coco
3937 lines
159 KiB
Plaintext
3937 lines
159 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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" *早早孕试纸机器学习算法验证*"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**import moudle**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import pandas as pd \n",
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"import seaborn as sns\n",
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"from IPython.display import display\n",
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"import matplotlib.pyplot as plt\n",
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"from mpl_toolkits.mplot3d import Axes3D\n",
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"import sklearn\n",
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"%matplotlib inline\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**load data**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"ename": "SyntaxError",
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"evalue": "Missing parentheses in call to 'print' (<ipython-input-2-3b119a451fc2>, line 14)",
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"output_type": "error",
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"traceback": [
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"\u001b[0;36m File \u001b[0;32m\"<ipython-input-2-3b119a451fc2>\"\u001b[0;36m, line \u001b[0;32m14\u001b[0m\n\u001b[0;31m print \"load data successful !!!!!\"\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m Missing parentheses in call to 'print'\n"
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]
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}
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],
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"source": [
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"try :\n",
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"# data_iphone6p_75_10 = pd.read_csv(\"20170912.pm.csv\")\n",
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"# data_iphone6p_1234 = pd.read_csv(\"20170920.pm.csv\")\n",
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"# data_iphone6p_5 = pd.read_csv(\"20170922.pm.csv\")\n",
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"# data_iphone6p_0 = pd.read_csv(\"20170925.am.csv\")\n",
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"# data_iphone6p_0_0 = pd.read_csv(\"20170925.pm.csv\")\n",
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"# data_iphone6p_246 = pd.read_csv(\"20171011.pm.csv\")\n",
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" \n",
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" data1 = pd.read_csv(\"light.csv\")\n",
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" data2 = pd.read_csv(\"nature_light.csv\")\n",
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"# data_test1 = pd.read_csv(\"./newData/test.csv\")\n",
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"# data_test2 = pd.read_csv(\"./newData/nubia_test.csv\")\n",
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" \n",
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" print \"load data successful !!!!!\"\n",
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"except :\n",
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" print \"load data error !!!!!!!!!!\""
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**分析数据**"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'data1' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m<ipython-input-3-3728f6a23dca>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;31m#data_all = data2.append(data1[data1[\"index\"] == 5 ]).append(data3).append(data1[data1[\"index\"] == 7 ]).append(data1[data1[\"index\"] == 8 ]).append(data0).append(data0_0).append(data4)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mdata1_0\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdata1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"whiteBalance\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 12\u001b[0m \u001b[0mdata2_0\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdata2\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"whiteBalance\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;31m#data_test_0 = data_test\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;31mNameError\u001b[0m: name 'data1' is not defined"
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]
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}
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],
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"source": [
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"# data4 = data_iphone6p_246[data_iphone6p_246[\"whiteBalance\"] == 0]\n",
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"# data2= data_iphone6p_1234[data_iphone6p_1234[\"whiteBalance\"] == 0 ]\n",
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"# data1 = data_iphone6p_75_10[data_iphone6p_75_10[\"whiteBalance\"] == 0 ]\n",
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"# data3 = data_iphone6p_5[data_iphone6p_5[\"whiteBalance\"] == 0]\n",
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"# data0 = data_iphone6p_0[data_iphone6p_0[\"whiteBalance\"] == 0]\n",
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"# data0_0 = data_iphone6p_0_0[data_iphone6p_0_0[\"whiteBalance\"] == 0]\n",
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"\n",
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"\n",
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"#data_all = data2.append(data1[data1[\"index\"] == 5 ]).append(data3).append(data1[data1[\"index\"] == 7 ]).append(data1[data1[\"index\"] == 8 ]).append(data0).append(data0_0).append(data4)\n",
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"\n",
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"data1_0 = data1[data1[\"whiteBalance\"] == 0]\n",
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"data2_0 = data2[data2[\"whiteBalance\"] == 0]\n",
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"#data_test_0 = data_test\n",
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"\n",
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"data_all =data1_0.append(data2_0);\n",
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"#data_all =data1.append(data2);\n",
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"#data_all = data2\n",
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"whiteBlock_R_one = data_all[data_all[\"index\"] == 0 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_one = data_all[data_all[\"index\"] == 0 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_one = data_all[data_all[\"index\"] == 0 ][\"left_block_B_stddev\"]\n",
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"\n",
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"whiteBlock_R_two = data_all[data_all[\"index\"] == 1 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_two = data_all[data_all[\"index\"] == 1 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_two = data_all[data_all[\"index\"] == 1 ][\"left_block_B_stddev\"]\n",
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"\n",
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"whiteBlock_R_three = data_all[data_all[\"index\"] == 2 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_three = data_all[data_all[\"index\"] == 2 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_three = data_all[data_all[\"index\"] == 2 ][\"left_block_B_stddev\"]\n",
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"\n",
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"whiteBlock_R_four = data_all[data_all[\"index\"] == 3 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_four = data_all[data_all[\"index\"] == 3 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_four = data_all[data_all[\"index\"] == 3 ][\"left_block_B_stddev\"]\n",
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"\n",
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"\n",
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"whiteBlock_R_five = data_all[data_all[\"index\"] == 4 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_five = data_all[data_all[\"index\"] == 4 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_five = data_all[data_all[\"index\"] == 4 ][\"left_block_B_stddev\"]\n",
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"\n",
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"whiteBlock_R_six = data_all[data_all[\"index\"] == 5 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_six = data_all[data_all[\"index\"] == 5 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_six = data_all[data_all[\"index\"] == 5 ][\"left_block_B_stddev\"]\n",
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"\n",
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"whiteBlock_R_seven = data_all[data_all[\"index\"] == 6 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_seven = data_all[data_all[\"index\"] == 6 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_seven = data_all[data_all[\"index\"] == 6 ][\"left_block_B_stddev\"]\n",
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"\n",
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"whiteBlock_R_eghit = data_all[data_all[\"index\"] == 7 ][\"left_block_R_stddev\"]\n",
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"whiteBlock_G_eghit = data_all[data_all[\"index\"] == 7 ][\"left_block_G_stddev\"]\n",
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"whiteBlock_B_eghit = data_all[data_all[\"index\"] == 7 ][\"left_block_B_stddev\"]\n",
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"\n",
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"print(data_all.describe())\n"
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]
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},
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{
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||
"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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||
{
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"data": {
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"text/plain": [
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||
"Index([u'dateTime', u'left_block_R', u'left_block_G', u'left_block_B', u'left_block_H', u'left_block_S', u'left_block_V', u'left_block_l', u'left_block_a', u'left_block_b', u'left_block_R_stddev', u'left_block_G_stddev', u'left_block_B_stddev', u'left_block_H_stddev', u'left_block_S_stddev', u'left_block_V_stddev', u'left_block_l_stddev', u'left_block_a_stddev', u'left_block_b_stddev', u'left_block_R_hist', u'left_block_G_hist', u'left_block_B_hist', u'left_block_H_hist', u'left_block_S_hist', u'left_block_V_hist', u'left_block_l_hist', u'left_block_a_hist', u'left_block_b_hist', u'left_block_R_max', u'left_block_G_max', u'left_block_B_max', u'left_block_H_max', u'left_block_S_max', u'left_block_V_max', u'left_block_l_max', u'left_block_a_max', u'left_block_b_max', u'left_block_R_min', u'left_block_G_min', u'left_block_B_min', u'left_block_H_min', u'left_block_S_min', u'left_block_V_min', u'left_block_l_min', u'left_block_a_min', u'left_block_b_min', u'right_block_R', u'right_block_G', u'right_block_B', u'right_block_H', u'right_block_S', u'right_block_V', u'right_block_l', u'right_block_a', u'right_block_b', u'right_block_R_stddev', u'right_block_G_stddev', u'right_block_B_stddev', u'right_block_H_stddev', u'right_block_S_stddev', u'right_block_V_stddev', u'right_block_l_stddev', u'right_block_a_stddev', u'right_block_b_stddev', u'right_block_R_hist', u'right_block_G_hist', u'right_block_B_hist', u'right_block_H_hist', u'right_block_S_hist', u'right_block_V_hist', u'right_block_l_hist', u'right_block_a_hist', u'right_block_b_hist', u'right_block_R_max', u'right_block_G_max', u'right_block_B_max', u'right_block_H_max', u'right_block_S_max', u'right_block_V_max', u'right_block_l_max', u'right_block_a_max', u'right_block_b_max', u'right_block_R_min', u'right_block_G_min', u'right_block_B_min', u'right_block_H_min', u'right_block_S_min', u'right_block_V_min', u'right_block_l_min', u'right_block_a_min', u'right_block_b_min', u'whiteBlock_R', u'whiteBlock_G', u'whiteBlock_B', u'whiteBlock_H', u'whiteBlock_S', u'whiteBlock_V', u'whiteBlock_l', u'whiteBlock_a', u'whiteBlock_b', ...], dtype='object')"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"data_all.columns"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": true
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},
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"source": [
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"hsv max min hist value h值要去掉"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>left_block_R</th>\n",
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" <th>left_block_G</th>\n",
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" <th>left_block_B</th>\n",
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" <th>left_block_H</th>\n",
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" <th>left_block_S</th>\n",
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" <th>left_block_V</th>\n",
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" <th>left_block_l</th>\n",
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" <th>left_block_a</th>\n",
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" <th>left_block_b</th>\n",
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" <th>left_block_R_stddev</th>\n",
|
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" <th>left_block_G_stddev</th>\n",
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" <th>left_block_B_stddev</th>\n",
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" <th>left_block_H_stddev</th>\n",
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" <th>left_block_S_stddev</th>\n",
|
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" <th>left_block_V_stddev</th>\n",
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" <th>left_block_l_stddev</th>\n",
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" <th>left_block_a_stddev</th>\n",
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" <th>left_block_b_stddev</th>\n",
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" <th>left_block_R_hist</th>\n",
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" <th>left_block_G_hist</th>\n",
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" <th></th>\n",
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" </tr>\n",
|
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>count</th>\n",
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||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td> 165.729696</td>\n",
|
||
" <td> 134.358506</td>\n",
|
||
" <td> 140.457706</td>\n",
|
||
" <td> 178.764099</td>\n",
|
||
" <td> 56.932838</td>\n",
|
||
" <td> 166.771580</td>\n",
|
||
" <td> 150.273458</td>\n",
|
||
" <td> 140.877241</td>\n",
|
||
" <td> 129.089342</td>\n",
|
||
" <td> 11.584725</td>\n",
|
||
" <td> 20.070492</td>\n",
|
||
" <td> 15.906036</td>\n",
|
||
" <td> 68.572622</td>\n",
|
||
" <td> 18.027338</td>\n",
|
||
" <td> 11.597200</td>\n",
|
||
" <td> 17.160557</td>\n",
|
||
" <td> 4.237259</td>\n",
|
||
" <td> 0.840747</td>\n",
|
||
" <td> 160.992618</td>\n",
|
||
" <td> 123.221520</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td> 30.728156</td>\n",
|
||
" <td> 39.645554</td>\n",
|
||
" <td> 35.580123</td>\n",
|
||
" <td> 62.957946</td>\n",
|
||
" <td> 28.703214</td>\n",
|
||
" <td> 31.214224</td>\n",
|
||
" <td> 35.806975</td>\n",
|
||
" <td> 7.556304</td>\n",
|
||
" <td> 2.173696</td>\n",
|
||
" <td> 8.180077</td>\n",
|
||
" <td> 11.086751</td>\n",
|
||
" <td> 9.979590</td>\n",
|
||
" <td> 37.974290</td>\n",
|
||
" <td> 11.795136</td>\n",
|
||
" <td> 8.177179</td>\n",
|
||
" <td> 10.284627</td>\n",
|
||
" <td> 1.908351</td>\n",
|
||
" <td> 0.495328</td>\n",
|
||
" <td> 35.854722</td>\n",
|
||
" <td> 50.745105</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td> 90.000000</td>\n",
|
||
" <td> 51.000000</td>\n",
|
||
" <td> 60.000000</td>\n",
|
||
" <td> 7.000000</td>\n",
|
||
" <td> 7.000000</td>\n",
|
||
" <td> 90.000000</td>\n",
|
||
" <td> 67.000000</td>\n",
|
||
" <td> 124.000000</td>\n",
|
||
" <td> 122.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 61.000000</td>\n",
|
||
" <td> 23.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td> 145.000000</td>\n",
|
||
" <td> 103.000000</td>\n",
|
||
" <td> 114.000000</td>\n",
|
||
" <td> 143.000000</td>\n",
|
||
" <td> 31.000000</td>\n",
|
||
" <td> 146.000000</td>\n",
|
||
" <td> 124.000000</td>\n",
|
||
" <td> 135.000000</td>\n",
|
||
" <td> 128.000000</td>\n",
|
||
" <td> 4.000000</td>\n",
|
||
" <td> 9.000000</td>\n",
|
||
" <td> 6.000000</td>\n",
|
||
" <td> 43.000000</td>\n",
|
||
" <td> 7.000000</td>\n",
|
||
" <td> 4.000000</td>\n",
|
||
" <td> 7.000000</td>\n",
|
||
" <td> 3.000000</td>\n",
|
||
" <td> 1.000000</td>\n",
|
||
" <td> 138.000000</td>\n",
|
||
" <td> 80.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td> 165.000000</td>\n",
|
||
" <td> 135.000000</td>\n",
|
||
" <td> 140.000000</td>\n",
|
||
" <td> 202.000000</td>\n",
|
||
" <td> 51.000000</td>\n",
|
||
" <td> 166.000000</td>\n",
|
||
" <td> 152.000000</td>\n",
|
||
" <td> 141.000000</td>\n",
|
||
" <td> 129.000000</td>\n",
|
||
" <td> 11.000000</td>\n",
|
||
" <td> 21.000000</td>\n",
|
||
" <td> 16.000000</td>\n",
|
||
" <td> 72.000000</td>\n",
|
||
" <td> 17.000000</td>\n",
|
||
" <td> 11.000000</td>\n",
|
||
" <td> 17.000000</td>\n",
|
||
" <td> 5.000000</td>\n",
|
||
" <td> 1.000000</td>\n",
|
||
" <td> 163.000000</td>\n",
|
||
" <td> 127.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td> 186.000000</td>\n",
|
||
" <td> 165.000000</td>\n",
|
||
" <td> 167.000000</td>\n",
|
||
" <td> 228.000000</td>\n",
|
||
" <td> 83.000000</td>\n",
|
||
" <td> 188.000000</td>\n",
|
||
" <td> 177.000000</td>\n",
|
||
" <td> 148.000000</td>\n",
|
||
" <td> 131.000000</td>\n",
|
||
" <td> 18.000000</td>\n",
|
||
" <td> 28.000000</td>\n",
|
||
" <td> 23.000000</td>\n",
|
||
" <td> 100.000000</td>\n",
|
||
" <td> 27.000000</td>\n",
|
||
" <td> 18.000000</td>\n",
|
||
" <td> 24.000000</td>\n",
|
||
" <td> 6.000000</td>\n",
|
||
" <td> 1.000000</td>\n",
|
||
" <td> 186.000000</td>\n",
|
||
" <td> 168.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td> 247.000000</td>\n",
|
||
" <td> 230.000000</td>\n",
|
||
" <td> 233.000000</td>\n",
|
||
" <td> 248.000000</td>\n",
|
||
" <td> 119.000000</td>\n",
|
||
" <td> 247.000000</td>\n",
|
||
" <td> 231.000000</td>\n",
|
||
" <td> 154.000000</td>\n",
|
||
" <td> 135.000000</td>\n",
|
||
" <td> 36.000000</td>\n",
|
||
" <td> 50.000000</td>\n",
|
||
" <td> 43.000000</td>\n",
|
||
" <td> 124.000000</td>\n",
|
||
" <td> 51.000000</td>\n",
|
||
" <td> 36.000000</td>\n",
|
||
" <td> 44.000000</td>\n",
|
||
" <td> 10.000000</td>\n",
|
||
" <td> 3.000000</td>\n",
|
||
" <td> 253.000000</td>\n",
|
||
" <td> 236.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>8 rows × 150 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" left_block_R left_block_G left_block_B left_block_H left_block_S \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean 165.729696 134.358506 140.457706 178.764099 56.932838 \n",
|
||
"std 30.728156 39.645554 35.580123 62.957946 28.703214 \n",
|
||
"min 90.000000 51.000000 60.000000 7.000000 7.000000 \n",
|
||
"25% 145.000000 103.000000 114.000000 143.000000 31.000000 \n",
|
||
"50% 165.000000 135.000000 140.000000 202.000000 51.000000 \n",
|
||
"75% 186.000000 165.000000 167.000000 228.000000 83.000000 \n",
|
||
"max 247.000000 230.000000 233.000000 248.000000 119.000000 \n",
|
||
"\n",
|
||
" left_block_V left_block_l left_block_a left_block_b \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean 166.771580 150.273458 140.877241 129.089342 \n",
|
||
"std 31.214224 35.806975 7.556304 2.173696 \n",
|
||
"min 90.000000 67.000000 124.000000 122.000000 \n",
|
||
"25% 146.000000 124.000000 135.000000 128.000000 \n",
|
||
"50% 166.000000 152.000000 141.000000 129.000000 \n",
|
||
"75% 188.000000 177.000000 148.000000 131.000000 \n",
|
||
"max 247.000000 231.000000 154.000000 135.000000 \n",
|
||
"\n",
|
||
" left_block_R_stddev left_block_G_stddev left_block_B_stddev \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean 11.584725 20.070492 15.906036 \n",
|
||
"std 8.180077 11.086751 9.979590 \n",
|
||
"min 0.000000 0.000000 0.000000 \n",
|
||
"25% 4.000000 9.000000 6.000000 \n",
|
||
"50% 11.000000 21.000000 16.000000 \n",
|
||
"75% 18.000000 28.000000 23.000000 \n",
|
||
"max 36.000000 50.000000 43.000000 \n",
|
||
"\n",
|
||
" left_block_H_stddev left_block_S_stddev left_block_V_stddev \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean 68.572622 18.027338 11.597200 \n",
|
||
"std 37.974290 11.795136 8.177179 \n",
|
||
"min 0.000000 0.000000 0.000000 \n",
|
||
"25% 43.000000 7.000000 4.000000 \n",
|
||
"50% 72.000000 17.000000 11.000000 \n",
|
||
"75% 100.000000 27.000000 18.000000 \n",
|
||
"max 124.000000 51.000000 36.000000 \n",
|
||
"\n",
|
||
" left_block_l_stddev left_block_a_stddev left_block_b_stddev \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean 17.160557 4.237259 0.840747 \n",
|
||
"std 10.284627 1.908351 0.495328 \n",
|
||
"min 0.000000 0.000000 0.000000 \n",
|
||
"25% 7.000000 3.000000 1.000000 \n",
|
||
"50% 17.000000 5.000000 1.000000 \n",
|
||
"75% 24.000000 6.000000 1.000000 \n",
|
||
"max 44.000000 10.000000 3.000000 \n",
|
||
"\n",
|
||
" left_block_R_hist left_block_G_hist \n",
|
||
"count 91301.000000 91301.000000 ... \n",
|
||
"mean 160.992618 123.221520 ... \n",
|
||
"std 35.854722 50.745105 ... \n",
|
||
"min 61.000000 23.000000 ... \n",
|
||
"25% 138.000000 80.000000 ... \n",
|
||
"50% 163.000000 127.000000 ... \n",
|
||
"75% 186.000000 168.000000 ... \n",
|
||
"max 253.000000 236.000000 ... \n",
|
||
"\n",
|
||
"[8 rows x 150 columns]"
|
||
]
|
||
},
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"\n",
|
||
"train_labels = data_all[\"index\"]\n",
|
||
"train_features = data_all.drop(\"dateTime\",axis=1)\n",
|
||
"train_features = train_features.drop(\"index\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBalance\",axis=1)\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features.describe()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"train_features = train_features.drop(\"left_block_H\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V\",axis=1)\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_min\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_min\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_min\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_min\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_min\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_min\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_min\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_min\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_min\",axis=1)\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features['lelf_right_R'] = train_features['left_block_R'] - train_features['right_block_R']\n",
|
||
"train_features['lelf_right_G'] = train_features['left_block_G'] - train_features['right_block_G']\n",
|
||
"train_features['lelf_right_B'] = train_features['left_block_B'] - train_features['right_block_B']\n",
|
||
"\n",
|
||
"# train_features['lelf_right_H'] = train_features['left_block_H'] - train_features['right_block_H']\n",
|
||
"# train_features['lelf_right_S'] = train_features['left_block_S'] - train_features['right_block_S']\n",
|
||
"# train_features['lelf_right_V'] = train_features['left_block_V'] - train_features['right_block_V']\n",
|
||
"\n",
|
||
"train_features['lelf_right_l'] = train_features['left_block_l'] - train_features['right_block_l']\n",
|
||
"train_features['lelf_right_a'] = train_features['left_block_a'] - train_features['right_block_a']\n",
|
||
"train_features['lelf_right_b'] = train_features['left_block_b'] - train_features['right_block_b']\n",
|
||
"\n",
|
||
"train_features['lelf_right_R_stddev'] = train_features['left_block_R_stddev'] - train_features['right_block_R_stddev']\n",
|
||
"train_features['lelf_right_G_stddev'] = train_features['left_block_G_stddev'] - train_features['right_block_G_stddev']\n",
|
||
"train_features['lelf_right_B_stddev'] = train_features['left_block_B_stddev'] - train_features['right_block_B_stddev']\n",
|
||
"\n",
|
||
"# train_features['lelf_right_H_stddev'] = train_features['left_block_H_stddev'] - train_features['right_block_H_stddev']\n",
|
||
"# train_features['lelf_right_S_stddev'] = train_features['left_block_S_stddev'] - train_features['right_block_S_stddev']\n",
|
||
"# train_features['lelf_right_V_stddev'] = train_features['left_block_V_stddev'] - train_features['right_block_V_stddev']\n",
|
||
"\n",
|
||
"train_features['lelf_right_l_stddev'] = train_features['left_block_l_stddev'] - train_features['right_block_l_stddev']\n",
|
||
"train_features['lelf_right_a_stddev'] = train_features['left_block_a_stddev'] - train_features['right_block_a_stddev']\n",
|
||
"train_features['lelf_right_b_stddev'] = train_features['left_block_b_stddev'] - train_features['right_block_b_stddev']\n",
|
||
"\n",
|
||
"train_features['lelf_right_R_hist'] = train_features['left_block_R_hist'] - train_features['right_block_R_hist']\n",
|
||
"train_features['lelf_right_G_hist'] = train_features['left_block_G_hist'] - train_features['right_block_G_hist']\n",
|
||
"train_features['lelf_right_B_hist'] = train_features['left_block_B_hist'] - train_features['right_block_B_hist']\n",
|
||
"\n",
|
||
"# train_features['lelf_right_H_hist'] = train_features['left_block_H_hist'] - train_features['right_block_H_hist']\n",
|
||
"# train_features['lelf_right_S_hist'] = train_features['left_block_S_hist'] - train_features['right_block_S_hist']\n",
|
||
"# train_features['lelf_right_V_hist'] = train_features['left_block_V_hist'] - train_features['right_block_V_hist']\n",
|
||
"\n",
|
||
"train_features['lelf_right_l_hist'] = train_features['left_block_l_hist'] - train_features['right_block_l_hist']\n",
|
||
"train_features['lelf_right_a_hist'] = train_features['left_block_a_hist'] - train_features['right_block_a_hist']\n",
|
||
"train_features['lelf_right_b_hist'] = train_features['left_block_b_hist'] - train_features['right_block_b_hist']\n",
|
||
"\n",
|
||
"train_features['lelf_right_R_max'] = train_features['left_block_R_max'] - train_features['right_block_R_max']\n",
|
||
"train_features['lelf_right_G_max'] = train_features['left_block_G_max'] - train_features['right_block_G_max']\n",
|
||
"train_features['lelf_right_B_max'] = train_features['left_block_B_max'] - train_features['right_block_B_max']\n",
|
||
"\n",
|
||
"# train_features['lelf_right_H_max'] = train_features['left_block_H_max'] - train_features['right_block_H_max']\n",
|
||
"# train_features['lelf_right_S_max'] = train_features['left_block_S_max'] - train_features['right_block_S_max']\n",
|
||
"# train_features['lelf_right_V_max'] = train_features['left_block_V_max'] - train_features['right_block_V_max']\n",
|
||
"\n",
|
||
"train_features['lelf_right_l_max'] = train_features['left_block_l_max'] - train_features['right_block_l_max']\n",
|
||
"train_features['lelf_right_a_max'] = train_features['left_block_a_max'] - train_features['right_block_a_max']\n",
|
||
"train_features['lelf_right_b_max'] = train_features['left_block_b_max'] - train_features['right_block_b_max']\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features['lelf_right_R_min'] = train_features['left_block_R_min'] - train_features['right_block_R_min']\n",
|
||
"train_features['lelf_right_G_min'] = train_features['left_block_G_min'] - train_features['right_block_G_min']\n",
|
||
"train_features['lelf_right_B_min'] = train_features['left_block_B_min'] - train_features['right_block_B_min']\n",
|
||
"\n",
|
||
"# train_features['lelf_right_H_min'] = train_features['left_block_H_min'] - train_features['right_block_H_min']\n",
|
||
"# train_features['lelf_right_S_min'] = train_features['left_block_S_min'] - train_features['right_block_S_min']\n",
|
||
"# train_features['lelf_right_V_min'] = train_features['left_block_V_min'] - train_features['right_block_V_min']\n",
|
||
"\n",
|
||
"train_features['lelf_right_l_min'] = train_features['left_block_l_min'] - train_features['right_block_l_min']\n",
|
||
"train_features['lelf_right_a_min'] = train_features['left_block_a_min'] - train_features['right_block_a_min']\n",
|
||
"train_features['lelf_right_b_min'] = train_features['left_block_b_min'] - train_features['right_block_b_min']\n",
|
||
"\n",
|
||
"train_features['lelf_right_gray_value'] = train_features['left_grayValue'] - train_features['right_grayValue']\n",
|
||
"train_features['lelf_right_gray_stddev'] = train_features['left_grayStddevValue'] - train_features['right_grayStddevValue']\n",
|
||
"train_features['lelf_right_gray_hist'] = train_features['left_grayHist'] - train_features['right_grayHist']\n",
|
||
"train_features['lelf_right_gray_max'] = train_features['left_grayMax'] - train_features['right_grayMax']\n",
|
||
"train_features['lelf_right_gray_min'] = train_features['left_grayMin'] - train_features['right_grayMin']\n",
|
||
"train_features.describe()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"metadata": {
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>lelf_right_R</th>\n",
|
||
" <th>lelf_right_G</th>\n",
|
||
" <th>lelf_right_B</th>\n",
|
||
" <th>lelf_right_H</th>\n",
|
||
" <th>lelf_right_S</th>\n",
|
||
" <th>lelf_right_V</th>\n",
|
||
" <th>lelf_right_l</th>\n",
|
||
" <th>lelf_right_a</th>\n",
|
||
" <th>lelf_right_b</th>\n",
|
||
" <th>lelf_right_R_stddev</th>\n",
|
||
" <th>lelf_right_G_stddev</th>\n",
|
||
" <th>lelf_right_B_stddev</th>\n",
|
||
" <th>lelf_right_H_stddev</th>\n",
|
||
" <th>lelf_right_S_stddev</th>\n",
|
||
" <th>lelf_right_V_stddev</th>\n",
|
||
" <th>lelf_right_l_stddev</th>\n",
|
||
" <th>lelf_right_a_stddev</th>\n",
|
||
" <th>lelf_right_b_stddev</th>\n",
|
||
" <th>lelf_right_R_hist</th>\n",
|
||
" <th>lelf_right_G_hist</th>\n",
|
||
" <th></th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>count</th>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td> 91301.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td> 1.262549</td>\n",
|
||
" <td> 11.583499</td>\n",
|
||
" <td> 8.142594</td>\n",
|
||
" <td> -30.762193</td>\n",
|
||
" <td> -11.383139</td>\n",
|
||
" <td> 2.284028</td>\n",
|
||
" <td> 8.190655</td>\n",
|
||
" <td> -4.545503</td>\n",
|
||
" <td> 0.222155</td>\n",
|
||
" <td> -1.514967</td>\n",
|
||
" <td> -5.195452</td>\n",
|
||
" <td> -3.733223</td>\n",
|
||
" <td> -3.283907</td>\n",
|
||
" <td> -6.145836</td>\n",
|
||
" <td> -1.526018</td>\n",
|
||
" <td> -3.821097</td>\n",
|
||
" <td> -1.773880</td>\n",
|
||
" <td> -0.021993</td>\n",
|
||
" <td> 2.052803</td>\n",
|
||
" <td> 16.861217</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td> 27.838211</td>\n",
|
||
" <td> 44.035454</td>\n",
|
||
" <td> 37.026650</td>\n",
|
||
" <td> 64.432921</td>\n",
|
||
" <td> 35.029158</td>\n",
|
||
" <td> 29.075898</td>\n",
|
||
" <td> 38.617100</td>\n",
|
||
" <td> 8.653738</td>\n",
|
||
" <td> 1.352848</td>\n",
|
||
" <td> 9.775919</td>\n",
|
||
" <td> 13.286977</td>\n",
|
||
" <td> 11.913398</td>\n",
|
||
" <td> 35.998510</td>\n",
|
||
" <td> 15.019288</td>\n",
|
||
" <td> 9.798269</td>\n",
|
||
" <td> 12.313324</td>\n",
|
||
" <td> 2.360502</td>\n",
|
||
" <td> 0.581796</td>\n",
|
||
" <td> 35.646931</td>\n",
|
||
" <td> 59.786437</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td> -52.000000</td>\n",
|
||
" <td> -63.000000</td>\n",
|
||
" <td> -54.000000</td>\n",
|
||
" <td> -222.000000</td>\n",
|
||
" <td> -84.000000</td>\n",
|
||
" <td> -52.000000</td>\n",
|
||
" <td> -56.000000</td>\n",
|
||
" <td> -25.000000</td>\n",
|
||
" <td> -4.000000</td>\n",
|
||
" <td> -18.000000</td>\n",
|
||
" <td> -37.000000</td>\n",
|
||
" <td> -31.000000</td>\n",
|
||
" <td> -108.000000</td>\n",
|
||
" <td> -35.000000</td>\n",
|
||
" <td> -19.000000</td>\n",
|
||
" <td> -30.000000</td>\n",
|
||
" <td> -9.000000</td>\n",
|
||
" <td> -2.000000</td>\n",
|
||
" <td> -110.000000</td>\n",
|
||
" <td> -134.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td> -26.000000</td>\n",
|
||
" <td> -33.000000</td>\n",
|
||
" <td> -29.000000</td>\n",
|
||
" <td> -76.000000</td>\n",
|
||
" <td> -43.000000</td>\n",
|
||
" <td> -26.000000</td>\n",
|
||
" <td> -30.000000</td>\n",
|
||
" <td> -11.000000</td>\n",
|
||
" <td> -1.000000</td>\n",
|
||
" <td> -11.000000</td>\n",
|
||
" <td> -18.000000</td>\n",
|
||
" <td> -15.000000</td>\n",
|
||
" <td> -30.000000</td>\n",
|
||
" <td> -20.000000</td>\n",
|
||
" <td> -11.000000</td>\n",
|
||
" <td> -16.000000</td>\n",
|
||
" <td> -4.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> -33.000000</td>\n",
|
||
" <td> -43.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td> 12.000000</td>\n",
|
||
" <td> 22.000000</td>\n",
|
||
" <td> 20.000000</td>\n",
|
||
" <td> -7.000000</td>\n",
|
||
" <td> -20.000000</td>\n",
|
||
" <td> 12.000000</td>\n",
|
||
" <td> 19.000000</td>\n",
|
||
" <td> -5.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> -4.000000</td>\n",
|
||
" <td> -6.000000</td>\n",
|
||
" <td> -5.000000</td>\n",
|
||
" <td> -9.000000</td>\n",
|
||
" <td> -8.000000</td>\n",
|
||
" <td> -4.000000</td>\n",
|
||
" <td> -5.000000</td>\n",
|
||
" <td> -2.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 12.000000</td>\n",
|
||
" <td> 27.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td> 26.000000</td>\n",
|
||
" <td> 52.000000</td>\n",
|
||
" <td> 42.000000</td>\n",
|
||
" <td> 18.000000</td>\n",
|
||
" <td> 22.000000</td>\n",
|
||
" <td> 29.000000</td>\n",
|
||
" <td> 44.000000</td>\n",
|
||
" <td> 3.000000</td>\n",
|
||
" <td> 1.000000</td>\n",
|
||
" <td> 8.000000</td>\n",
|
||
" <td> 8.000000</td>\n",
|
||
" <td> 8.000000</td>\n",
|
||
" <td> 24.000000</td>\n",
|
||
" <td> 9.000000</td>\n",
|
||
" <td> 8.000000</td>\n",
|
||
" <td> 8.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 0.000000</td>\n",
|
||
" <td> 30.000000</td>\n",
|
||
" <td> 69.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td> 52.000000</td>\n",
|
||
" <td> 99.000000</td>\n",
|
||
" <td> 79.000000</td>\n",
|
||
" <td> 152.000000</td>\n",
|
||
" <td> 46.000000</td>\n",
|
||
" <td> 60.000000</td>\n",
|
||
" <td> 80.000000</td>\n",
|
||
" <td> 13.000000</td>\n",
|
||
" <td> 5.000000</td>\n",
|
||
" <td> 19.000000</td>\n",
|
||
" <td> 19.000000</td>\n",
|
||
" <td> 19.000000</td>\n",
|
||
" <td> 118.000000</td>\n",
|
||
" <td> 24.000000</td>\n",
|
||
" <td> 19.000000</td>\n",
|
||
" <td> 20.000000</td>\n",
|
||
" <td> 4.000000</td>\n",
|
||
" <td> 2.000000</td>\n",
|
||
" <td> 90.000000</td>\n",
|
||
" <td> 153.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>8 rows × 50 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" lelf_right_R lelf_right_G lelf_right_B lelf_right_H lelf_right_S \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean 1.262549 11.583499 8.142594 -30.762193 -11.383139 \n",
|
||
"std 27.838211 44.035454 37.026650 64.432921 35.029158 \n",
|
||
"min -52.000000 -63.000000 -54.000000 -222.000000 -84.000000 \n",
|
||
"25% -26.000000 -33.000000 -29.000000 -76.000000 -43.000000 \n",
|
||
"50% 12.000000 22.000000 20.000000 -7.000000 -20.000000 \n",
|
||
"75% 26.000000 52.000000 42.000000 18.000000 22.000000 \n",
|
||
"max 52.000000 99.000000 79.000000 152.000000 46.000000 \n",
|
||
"\n",
|
||
" lelf_right_V lelf_right_l lelf_right_a lelf_right_b \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean 2.284028 8.190655 -4.545503 0.222155 \n",
|
||
"std 29.075898 38.617100 8.653738 1.352848 \n",
|
||
"min -52.000000 -56.000000 -25.000000 -4.000000 \n",
|
||
"25% -26.000000 -30.000000 -11.000000 -1.000000 \n",
|
||
"50% 12.000000 19.000000 -5.000000 0.000000 \n",
|
||
"75% 29.000000 44.000000 3.000000 1.000000 \n",
|
||
"max 60.000000 80.000000 13.000000 5.000000 \n",
|
||
"\n",
|
||
" lelf_right_R_stddev lelf_right_G_stddev lelf_right_B_stddev \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean -1.514967 -5.195452 -3.733223 \n",
|
||
"std 9.775919 13.286977 11.913398 \n",
|
||
"min -18.000000 -37.000000 -31.000000 \n",
|
||
"25% -11.000000 -18.000000 -15.000000 \n",
|
||
"50% -4.000000 -6.000000 -5.000000 \n",
|
||
"75% 8.000000 8.000000 8.000000 \n",
|
||
"max 19.000000 19.000000 19.000000 \n",
|
||
"\n",
|
||
" lelf_right_H_stddev lelf_right_S_stddev lelf_right_V_stddev \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean -3.283907 -6.145836 -1.526018 \n",
|
||
"std 35.998510 15.019288 9.798269 \n",
|
||
"min -108.000000 -35.000000 -19.000000 \n",
|
||
"25% -30.000000 -20.000000 -11.000000 \n",
|
||
"50% -9.000000 -8.000000 -4.000000 \n",
|
||
"75% 24.000000 9.000000 8.000000 \n",
|
||
"max 118.000000 24.000000 19.000000 \n",
|
||
"\n",
|
||
" lelf_right_l_stddev lelf_right_a_stddev lelf_right_b_stddev \\\n",
|
||
"count 91301.000000 91301.000000 91301.000000 \n",
|
||
"mean -3.821097 -1.773880 -0.021993 \n",
|
||
"std 12.313324 2.360502 0.581796 \n",
|
||
"min -30.000000 -9.000000 -2.000000 \n",
|
||
"25% -16.000000 -4.000000 0.000000 \n",
|
||
"50% -5.000000 -2.000000 0.000000 \n",
|
||
"75% 8.000000 0.000000 0.000000 \n",
|
||
"max 20.000000 4.000000 2.000000 \n",
|
||
"\n",
|
||
" lelf_right_R_hist lelf_right_G_hist \n",
|
||
"count 91301.000000 91301.000000 ... \n",
|
||
"mean 2.052803 16.861217 ... \n",
|
||
"std 35.646931 59.786437 ... \n",
|
||
"min -110.000000 -134.000000 ... \n",
|
||
"25% -33.000000 -43.000000 ... \n",
|
||
"50% 12.000000 27.000000 ... \n",
|
||
"75% 30.000000 69.000000 ... \n",
|
||
"max 90.000000 153.000000 ... \n",
|
||
"\n",
|
||
"[8 rows x 50 columns]"
|
||
]
|
||
},
|
||
"execution_count": 6,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"train_features_9 = pd.DataFrame()\n",
|
||
"train_features_9['lelf_right_R'] = train_features['left_block_R'] - train_features['right_block_R']\n",
|
||
"train_features_9['lelf_right_G'] = train_features['left_block_G'] - train_features['right_block_G']\n",
|
||
"train_features_9['lelf_right_B'] = train_features['left_block_B'] - train_features['right_block_B']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_H'] = train_features['left_block_H'] - train_features['right_block_H']\n",
|
||
"train_features_9['lelf_right_S'] = train_features['left_block_S'] - train_features['right_block_S']\n",
|
||
"train_features_9['lelf_right_V'] = train_features['left_block_V'] - train_features['right_block_V']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_l'] = train_features['left_block_l'] - train_features['right_block_l']\n",
|
||
"train_features_9['lelf_right_a'] = train_features['left_block_a'] - train_features['right_block_a']\n",
|
||
"train_features_9['lelf_right_b'] = train_features['left_block_b'] - train_features['right_block_b']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_R_stddev'] = train_features['left_block_R_stddev'] - train_features['right_block_R_stddev']\n",
|
||
"train_features_9['lelf_right_G_stddev'] = train_features['left_block_G_stddev'] - train_features['right_block_G_stddev']\n",
|
||
"train_features_9['lelf_right_B_stddev'] = train_features['left_block_B_stddev'] - train_features['right_block_B_stddev']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_H_stddev'] = train_features['left_block_H_stddev'] - train_features['right_block_H_stddev']\n",
|
||
"train_features_9['lelf_right_S_stddev'] = train_features['left_block_S_stddev'] - train_features['right_block_S_stddev']\n",
|
||
"train_features_9['lelf_right_V_stddev'] = train_features['left_block_V_stddev'] - train_features['right_block_V_stddev']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_l_stddev'] = train_features['left_block_l_stddev'] - train_features['right_block_l_stddev']\n",
|
||
"train_features_9['lelf_right_a_stddev'] = train_features['left_block_a_stddev'] - train_features['right_block_a_stddev']\n",
|
||
"train_features_9['lelf_right_b_stddev'] = train_features['left_block_b_stddev'] - train_features['right_block_b_stddev']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_R_hist'] = train_features['left_block_R_hist'] - train_features['right_block_R_hist']\n",
|
||
"train_features_9['lelf_right_G_hist'] = train_features['left_block_G_hist'] - train_features['right_block_G_hist']\n",
|
||
"train_features_9['lelf_right_B_hist'] = train_features['left_block_B_hist'] - train_features['right_block_B_hist']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_H_hist'] = train_features['left_block_H_hist'] - train_features['right_block_H_hist']\n",
|
||
"train_features_9['lelf_right_S_hist'] = train_features['left_block_S_hist'] - train_features['right_block_S_hist']\n",
|
||
"train_features_9['lelf_right_V_hist'] = train_features['left_block_V_hist'] - train_features['right_block_V_hist']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_l_hist'] = train_features['left_block_l_hist'] - train_features['right_block_l_hist']\n",
|
||
"train_features_9['lelf_right_a_hist'] = train_features['left_block_a_hist'] - train_features['right_block_a_hist']\n",
|
||
"train_features_9['lelf_right_b_hist'] = train_features['left_block_b_hist'] - train_features['right_block_b_hist']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_R_max'] = train_features['left_block_R_max'] - train_features['right_block_R_max']\n",
|
||
"train_features_9['lelf_right_G_max'] = train_features['left_block_G_max'] - train_features['right_block_G_max']\n",
|
||
"train_features_9['lelf_right_B_max'] = train_features['left_block_B_max'] - train_features['right_block_B_max']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_H_max'] = train_features['left_block_H_max'] - train_features['right_block_H_max']\n",
|
||
"train_features_9['lelf_right_S_max'] = train_features['left_block_S_max'] - train_features['right_block_S_max']\n",
|
||
"train_features_9['lelf_right_V_max'] = train_features['left_block_V_max'] - train_features['right_block_V_max']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_l_max'] = train_features['left_block_l_max'] - train_features['right_block_l_max']\n",
|
||
"train_features_9['lelf_right_a_max'] = train_features['left_block_a_max'] - train_features['right_block_a_max']\n",
|
||
"train_features_9['lelf_right_b_max'] = train_features['left_block_b_max'] - train_features['right_block_b_max']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_R_min'] = train_features['left_block_R_min'] - train_features['right_block_R_min']\n",
|
||
"train_features_9['lelf_right_G_min'] = train_features['left_block_G_min'] - train_features['right_block_G_min']\n",
|
||
"train_features_9['lelf_right_B_min'] = train_features['left_block_B_min'] - train_features['right_block_B_min']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_H_min'] = train_features['left_block_H_min'] - train_features['right_block_H_min']\n",
|
||
"train_features_9['lelf_right_S_min'] = train_features['left_block_S_min'] - train_features['right_block_S_min']\n",
|
||
"train_features_9['lelf_right_V_min'] = train_features['left_block_V_min'] - train_features['right_block_V_min']\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_l_min'] = train_features['left_block_l_min'] - train_features['right_block_l_min']\n",
|
||
"train_features_9['lelf_right_a_min'] = train_features['left_block_a_min'] - train_features['right_block_a_min']\n",
|
||
"train_features_9['lelf_right_b_min'] = train_features['left_block_b_min'] - train_features['right_block_b_min']\n",
|
||
"\n",
|
||
"# train_features_9['left_grayValue']= train_features['left_grayValue'];\n",
|
||
"# train_features_9['left_grayStddevValue']= train_features['left_grayStddevValue'];\n",
|
||
"# train_features_9['left_grayHist']= train_features['left_grayHist'];\n",
|
||
"# train_features_9['left_grayMax']= train_features['left_grayMax'];\n",
|
||
"# train_features_9['left_grayMin']= train_features['left_grayMin'];\n",
|
||
"\n",
|
||
"# train_features_9['right_grayValue']= train_features['right_grayValue'];\n",
|
||
"# train_features_9['right_grayStddevValue']= train_features['right_grayStddevValue'];\n",
|
||
"# train_features_9['right_grayHist']= train_features['right_grayHist'];\n",
|
||
"# train_features_9['right_grayMax']= train_features['right_grayMax'];\n",
|
||
"# train_features_9['right_grayMin']= train_features['right_grayMin'];\n",
|
||
"\n",
|
||
"# train_features_9['lelf_R_stddev'] = train_features['left_block_R_stddev'] \n",
|
||
"# train_features_9['lelf_G_stddev'] = train_features['left_block_G_stddev'] \n",
|
||
"# train_features_9['lelf_B_stddev'] = train_features['left_block_B_stddev'] \n",
|
||
"\n",
|
||
"# train_features_9['left_block_R_min'] = train_features['left_block_R_min'] \n",
|
||
"# train_features_9['left_block_G_min'] = train_features['left_block_G_min'] \n",
|
||
"# train_features_9['left_block_B_min'] = train_features['left_block_B_min'] \n",
|
||
"\n",
|
||
"\n",
|
||
"train_features_9['lelf_right_gray_value'] = train_features['left_grayValue'] - train_features['right_grayValue']\n",
|
||
"train_features_9['lelf_right_gray_stddev'] = train_features['left_grayStddevValue'] - train_features['right_grayStddevValue']\n",
|
||
"train_features_9['lelf_right_gray_hist'] = train_features['left_grayHist'] - train_features['right_grayHist']\n",
|
||
"train_features_9['lelf_right_gray_max'] = train_features['left_grayMax'] - train_features['right_grayMax']\n",
|
||
"train_features_9['lelf_right_gray_min'] = train_features['left_grayMin'] - train_features['right_grayMin']\n",
|
||
"#train_features_9['index'] = train_labels\n",
|
||
"train_features_9.describe()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"**去掉左边块的方差和白块和右边块的特征**"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"metadata": {
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style>\n",
|
||
" .dataframe thead tr:only-child th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: left;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>left_block_R</th>\n",
|
||
" <th>left_block_G</th>\n",
|
||
" <th>left_block_B</th>\n",
|
||
" <th>left_block_R_hist</th>\n",
|
||
" <th>left_block_G_hist</th>\n",
|
||
" <th>left_block_B_hist</th>\n",
|
||
" <th>left_block_R_max</th>\n",
|
||
" <th>left_block_G_max</th>\n",
|
||
" <th>left_block_B_max</th>\n",
|
||
" <th>right_block_R</th>\n",
|
||
" <th>right_block_G</th>\n",
|
||
" <th>right_block_B</th>\n",
|
||
" <th>right_block_R_hist</th>\n",
|
||
" <th>right_block_G_hist</th>\n",
|
||
" <th>right_block_B_hist</th>\n",
|
||
" <th>right_block_R_max</th>\n",
|
||
" <th>right_block_G_max</th>\n",
|
||
" <th>right_block_B_max</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>count</th>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td>178.697470</td>\n",
|
||
" <td>149.211462</td>\n",
|
||
" <td>156.498504</td>\n",
|
||
" <td>184.695405</td>\n",
|
||
" <td>155.233132</td>\n",
|
||
" <td>163.526025</td>\n",
|
||
" <td>199.778027</td>\n",
|
||
" <td>182.282382</td>\n",
|
||
" <td>182.766180</td>\n",
|
||
" <td>175.436182</td>\n",
|
||
" <td>134.494487</td>\n",
|
||
" <td>146.433846</td>\n",
|
||
" <td>171.109646</td>\n",
|
||
" <td>122.180043</td>\n",
|
||
" <td>137.949731</td>\n",
|
||
" <td>199.220391</td>\n",
|
||
" <td>176.936189</td>\n",
|
||
" <td>178.925115</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td>24.046505</td>\n",
|
||
" <td>31.729368</td>\n",
|
||
" <td>28.741443</td>\n",
|
||
" <td>23.740233</td>\n",
|
||
" <td>35.584197</td>\n",
|
||
" <td>29.305194</td>\n",
|
||
" <td>19.174077</td>\n",
|
||
" <td>21.953094</td>\n",
|
||
" <td>20.304439</td>\n",
|
||
" <td>19.894154</td>\n",
|
||
" <td>19.784332</td>\n",
|
||
" <td>21.177152</td>\n",
|
||
" <td>21.059931</td>\n",
|
||
" <td>23.465965</td>\n",
|
||
" <td>23.959939</td>\n",
|
||
" <td>18.239064</td>\n",
|
||
" <td>18.640658</td>\n",
|
||
" <td>18.174246</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td>15.000000</td>\n",
|
||
" <td>67.000000</td>\n",
|
||
" <td>36.000000</td>\n",
|
||
" <td>13.000000</td>\n",
|
||
" <td>30.000000</td>\n",
|
||
" <td>36.000000</td>\n",
|
||
" <td>31.000000</td>\n",
|
||
" <td>87.000000</td>\n",
|
||
" <td>45.000000</td>\n",
|
||
" <td>110.000000</td>\n",
|
||
" <td>76.000000</td>\n",
|
||
" <td>78.000000</td>\n",
|
||
" <td>108.000000</td>\n",
|
||
" <td>65.000000</td>\n",
|
||
" <td>69.000000</td>\n",
|
||
" <td>129.000000</td>\n",
|
||
" <td>109.000000</td>\n",
|
||
" <td>106.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td>164.000000</td>\n",
|
||
" <td>124.000000</td>\n",
|
||
" <td>135.000000</td>\n",
|
||
" <td>171.000000</td>\n",
|
||
" <td>132.000000</td>\n",
|
||
" <td>145.000000</td>\n",
|
||
" <td>192.000000</td>\n",
|
||
" <td>171.000000</td>\n",
|
||
" <td>171.000000</td>\n",
|
||
" <td>165.000000</td>\n",
|
||
" <td>123.000000</td>\n",
|
||
" <td>136.000000</td>\n",
|
||
" <td>159.000000</td>\n",
|
||
" <td>105.000000</td>\n",
|
||
" <td>125.000000</td>\n",
|
||
" <td>192.000000</td>\n",
|
||
" <td>168.000000</td>\n",
|
||
" <td>170.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td>180.000000</td>\n",
|
||
" <td>147.000000</td>\n",
|
||
" <td>158.000000</td>\n",
|
||
" <td>189.000000</td>\n",
|
||
" <td>161.000000</td>\n",
|
||
" <td>168.000000</td>\n",
|
||
" <td>201.000000</td>\n",
|
||
" <td>182.000000</td>\n",
|
||
" <td>184.000000</td>\n",
|
||
" <td>178.000000</td>\n",
|
||
" <td>136.000000</td>\n",
|
||
" <td>149.000000</td>\n",
|
||
" <td>173.000000</td>\n",
|
||
" <td>123.000000</td>\n",
|
||
" <td>140.000000</td>\n",
|
||
" <td>199.000000</td>\n",
|
||
" <td>176.000000</td>\n",
|
||
" <td>180.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td>194.000000</td>\n",
|
||
" <td>173.000000</td>\n",
|
||
" <td>177.000000</td>\n",
|
||
" <td>198.000000</td>\n",
|
||
" <td>181.000000</td>\n",
|
||
" <td>183.000000</td>\n",
|
||
" <td>209.000000</td>\n",
|
||
" <td>195.000000</td>\n",
|
||
" <td>195.000000</td>\n",
|
||
" <td>187.000000</td>\n",
|
||
" <td>148.000000</td>\n",
|
||
" <td>159.000000</td>\n",
|
||
" <td>185.000000</td>\n",
|
||
" <td>138.000000</td>\n",
|
||
" <td>154.000000</td>\n",
|
||
" <td>208.000000</td>\n",
|
||
" <td>187.000000</td>\n",
|
||
" <td>189.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td>253.000000</td>\n",
|
||
" <td>235.000000</td>\n",
|
||
" <td>244.000000</td>\n",
|
||
" <td>254.000000</td>\n",
|
||
" <td>254.000000</td>\n",
|
||
" <td>254.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>253.000000</td>\n",
|
||
" <td>220.000000</td>\n",
|
||
" <td>226.000000</td>\n",
|
||
" <td>254.000000</td>\n",
|
||
" <td>233.000000</td>\n",
|
||
" <td>232.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>254.000000</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" left_block_R left_block_G left_block_B left_block_R_hist \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 178.697470 149.211462 156.498504 184.695405 \n",
|
||
"std 24.046505 31.729368 28.741443 23.740233 \n",
|
||
"min 15.000000 67.000000 36.000000 13.000000 \n",
|
||
"25% 164.000000 124.000000 135.000000 171.000000 \n",
|
||
"50% 180.000000 147.000000 158.000000 189.000000 \n",
|
||
"75% 194.000000 173.000000 177.000000 198.000000 \n",
|
||
"max 253.000000 235.000000 244.000000 254.000000 \n",
|
||
"\n",
|
||
" left_block_G_hist left_block_B_hist left_block_R_max \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 155.233132 163.526025 199.778027 \n",
|
||
"std 35.584197 29.305194 19.174077 \n",
|
||
"min 30.000000 36.000000 31.000000 \n",
|
||
"25% 132.000000 145.000000 192.000000 \n",
|
||
"50% 161.000000 168.000000 201.000000 \n",
|
||
"75% 181.000000 183.000000 209.000000 \n",
|
||
"max 254.000000 254.000000 255.000000 \n",
|
||
"\n",
|
||
" left_block_G_max left_block_B_max right_block_R right_block_G \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 182.282382 182.766180 175.436182 134.494487 \n",
|
||
"std 21.953094 20.304439 19.894154 19.784332 \n",
|
||
"min 87.000000 45.000000 110.000000 76.000000 \n",
|
||
"25% 171.000000 171.000000 165.000000 123.000000 \n",
|
||
"50% 182.000000 184.000000 178.000000 136.000000 \n",
|
||
"75% 195.000000 195.000000 187.000000 148.000000 \n",
|
||
"max 255.000000 255.000000 253.000000 220.000000 \n",
|
||
"\n",
|
||
" right_block_B right_block_R_hist right_block_G_hist \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 146.433846 171.109646 122.180043 \n",
|
||
"std 21.177152 21.059931 23.465965 \n",
|
||
"min 78.000000 108.000000 65.000000 \n",
|
||
"25% 136.000000 159.000000 105.000000 \n",
|
||
"50% 149.000000 173.000000 123.000000 \n",
|
||
"75% 159.000000 185.000000 138.000000 \n",
|
||
"max 226.000000 254.000000 233.000000 \n",
|
||
"\n",
|
||
" right_block_B_hist right_block_R_max right_block_G_max \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 137.949731 199.220391 176.936189 \n",
|
||
"std 23.959939 18.239064 18.640658 \n",
|
||
"min 69.000000 129.000000 109.000000 \n",
|
||
"25% 125.000000 192.000000 168.000000 \n",
|
||
"50% 140.000000 199.000000 176.000000 \n",
|
||
"75% 154.000000 208.000000 187.000000 \n",
|
||
"max 232.000000 255.000000 255.000000 \n",
|
||
"\n",
|
||
" right_block_B_max \n",
|
||
"count 151086.000000 \n",
|
||
"mean 178.925115 \n",
|
||
"std 18.174246 \n",
|
||
"min 106.000000 \n",
|
||
"25% 170.000000 \n",
|
||
"50% 180.000000 \n",
|
||
"75% 189.000000 \n",
|
||
"max 254.000000 "
|
||
]
|
||
},
|
||
"execution_count": 24,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# train_features = train_features.drop(\"left_block_R\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_G\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_B\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"left_block_R_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_G_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_B_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"left_block_R_max\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_G_max\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_B_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_l\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_a\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_b\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_l_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_a_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_b_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_l_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_a_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_b_max\",axis=1)\n",
|
||
"##################################################################\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_R\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_G\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_B\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_R_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_G_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_B_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_R_max\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_G_max\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_B_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_l\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_a\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_b\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_l_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_a_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_b_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_l_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_a_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_b_max\",axis=1)\n",
|
||
"\n",
|
||
"####################################################################\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_R\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_G\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_B\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_R_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_G_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_B_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_R_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_G_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_B_max\",axis=1)\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_max\",axis=1)\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_l\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_a\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_b\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_l_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_a_hist\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_b_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_l_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_a_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_b_max\",axis=1)\n",
|
||
"\n",
|
||
"##################################################################\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features.describe()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"**去掉所有块的方差特征**"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_b_stddev\",axis=1)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"# train_features = train_features.drop(\"left_block_R\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_G\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_B\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"left_block_H\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_S\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_V\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"left_block_l\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_a\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_b\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_R\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_G\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_B\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_H\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_S\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_V\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_l\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_a\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_b\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_R\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_G\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_B\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_H\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_S\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_V\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_l\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_a\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_b\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"left_block_R_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_G_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_B_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"left_block_H_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_S_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"left_block_l_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_a_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"left_block_b_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_R_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_G_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_B_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_H_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_S_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"right_block_l_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_a_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"right_block_b_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_R_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_G_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_B_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_H_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_S_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_l_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_a_hist\",axis=1)\n",
|
||
"# train_features = train_features.drop(\"whiteBlock_b_hist\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_R_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_G_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_l_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_a_stddev\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_R_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_G_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_B_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"left_block_l_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_a_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"left_block_b_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_R_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_G_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_B_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"right_block_l_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_a_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"right_block_b_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_R_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_G_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_B_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_H_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_S_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_V_max\",axis=1)\n",
|
||
"\n",
|
||
"train_features = train_features.drop(\"whiteBlock_l_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_a_max\",axis=1)\n",
|
||
"train_features = train_features.drop(\"whiteBlock_b_max\",axis=1)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style>\n",
|
||
" .dataframe thead tr:only-child th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: left;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>left_block_R</th>\n",
|
||
" <th>left_block_G</th>\n",
|
||
" <th>left_block_B</th>\n",
|
||
" <th>left_block_H</th>\n",
|
||
" <th>left_block_S</th>\n",
|
||
" <th>left_block_V</th>\n",
|
||
" <th>left_block_l</th>\n",
|
||
" <th>left_block_a</th>\n",
|
||
" <th>left_block_b</th>\n",
|
||
" <th>left_block_R_hist</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th>whiteBlock_b_hist</th>\n",
|
||
" <th>whiteBlock_R_max</th>\n",
|
||
" <th>whiteBlock_G_max</th>\n",
|
||
" <th>whiteBlock_B_max</th>\n",
|
||
" <th>whiteBlock_H_max</th>\n",
|
||
" <th>whiteBlock_S_max</th>\n",
|
||
" <th>whiteBlock_V_max</th>\n",
|
||
" <th>whiteBlock_l_max</th>\n",
|
||
" <th>whiteBlock_a_max</th>\n",
|
||
" <th>whiteBlock_b_max</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>count</th>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" <td>151086.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td>178.697470</td>\n",
|
||
" <td>149.211462</td>\n",
|
||
" <td>156.498504</td>\n",
|
||
" <td>179.578862</td>\n",
|
||
" <td>48.304482</td>\n",
|
||
" <td>180.058682</td>\n",
|
||
" <td>164.499669</td>\n",
|
||
" <td>140.003925</td>\n",
|
||
" <td>127.971162</td>\n",
|
||
" <td>184.695405</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>130.782197</td>\n",
|
||
" <td>202.084376</td>\n",
|
||
" <td>192.246787</td>\n",
|
||
" <td>189.165853</td>\n",
|
||
" <td>85.140000</td>\n",
|
||
" <td>25.093086</td>\n",
|
||
" <td>203.718994</td>\n",
|
||
" <td>200.058430</td>\n",
|
||
" <td>132.367804</td>\n",
|
||
" <td>131.734747</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td>24.046505</td>\n",
|
||
" <td>31.729368</td>\n",
|
||
" <td>28.741443</td>\n",
|
||
" <td>76.696214</td>\n",
|
||
" <td>19.148976</td>\n",
|
||
" <td>23.796653</td>\n",
|
||
" <td>28.073481</td>\n",
|
||
" <td>5.934290</td>\n",
|
||
" <td>4.505780</td>\n",
|
||
" <td>23.740233</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>4.662874</td>\n",
|
||
" <td>19.940399</td>\n",
|
||
" <td>21.283803</td>\n",
|
||
" <td>21.176846</td>\n",
|
||
" <td>98.779586</td>\n",
|
||
" <td>11.144240</td>\n",
|
||
" <td>18.427383</td>\n",
|
||
" <td>19.261219</td>\n",
|
||
" <td>2.745161</td>\n",
|
||
" <td>4.569725</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td>15.000000</td>\n",
|
||
" <td>67.000000</td>\n",
|
||
" <td>36.000000</td>\n",
|
||
" <td>6.000000</td>\n",
|
||
" <td>2.000000</td>\n",
|
||
" <td>78.000000</td>\n",
|
||
" <td>73.000000</td>\n",
|
||
" <td>97.000000</td>\n",
|
||
" <td>105.000000</td>\n",
|
||
" <td>13.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>107.000000</td>\n",
|
||
" <td>125.000000</td>\n",
|
||
" <td>116.000000</td>\n",
|
||
" <td>107.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>125.000000</td>\n",
|
||
" <td>125.000000</td>\n",
|
||
" <td>127.000000</td>\n",
|
||
" <td>108.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td>164.000000</td>\n",
|
||
" <td>124.000000</td>\n",
|
||
" <td>135.000000</td>\n",
|
||
" <td>149.000000</td>\n",
|
||
" <td>35.000000</td>\n",
|
||
" <td>165.000000</td>\n",
|
||
" <td>143.000000</td>\n",
|
||
" <td>136.000000</td>\n",
|
||
" <td>127.000000</td>\n",
|
||
" <td>171.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>130.000000</td>\n",
|
||
" <td>193.000000</td>\n",
|
||
" <td>182.000000</td>\n",
|
||
" <td>179.000000</td>\n",
|
||
" <td>19.000000</td>\n",
|
||
" <td>17.000000</td>\n",
|
||
" <td>197.000000</td>\n",
|
||
" <td>190.000000</td>\n",
|
||
" <td>130.000000</td>\n",
|
||
" <td>131.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td>180.000000</td>\n",
|
||
" <td>147.000000</td>\n",
|
||
" <td>158.000000</td>\n",
|
||
" <td>217.000000</td>\n",
|
||
" <td>49.000000</td>\n",
|
||
" <td>181.000000</td>\n",
|
||
" <td>165.000000</td>\n",
|
||
" <td>142.000000</td>\n",
|
||
" <td>128.000000</td>\n",
|
||
" <td>189.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>131.000000</td>\n",
|
||
" <td>205.000000</td>\n",
|
||
" <td>196.000000</td>\n",
|
||
" <td>193.000000</td>\n",
|
||
" <td>27.000000</td>\n",
|
||
" <td>22.000000</td>\n",
|
||
" <td>205.000000</td>\n",
|
||
" <td>203.000000</td>\n",
|
||
" <td>132.000000</td>\n",
|
||
" <td>132.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td>194.000000</td>\n",
|
||
" <td>173.000000</td>\n",
|
||
" <td>177.000000</td>\n",
|
||
" <td>239.000000</td>\n",
|
||
" <td>65.000000</td>\n",
|
||
" <td>196.000000</td>\n",
|
||
" <td>184.000000</td>\n",
|
||
" <td>145.000000</td>\n",
|
||
" <td>130.000000</td>\n",
|
||
" <td>198.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>133.000000</td>\n",
|
||
" <td>212.000000</td>\n",
|
||
" <td>204.000000</td>\n",
|
||
" <td>201.000000</td>\n",
|
||
" <td>199.000000</td>\n",
|
||
" <td>32.000000</td>\n",
|
||
" <td>212.000000</td>\n",
|
||
" <td>210.000000</td>\n",
|
||
" <td>134.000000</td>\n",
|
||
" <td>134.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td>253.000000</td>\n",
|
||
" <td>235.000000</td>\n",
|
||
" <td>244.000000</td>\n",
|
||
" <td>247.000000</td>\n",
|
||
" <td>206.000000</td>\n",
|
||
" <td>253.000000</td>\n",
|
||
" <td>241.000000</td>\n",
|
||
" <td>151.000000</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>254.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>150.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>123.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>255.000000</td>\n",
|
||
" <td>158.000000</td>\n",
|
||
" <td>153.000000</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>8 rows × 81 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" left_block_R left_block_G left_block_B left_block_H \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 178.697470 149.211462 156.498504 179.578862 \n",
|
||
"std 24.046505 31.729368 28.741443 76.696214 \n",
|
||
"min 15.000000 67.000000 36.000000 6.000000 \n",
|
||
"25% 164.000000 124.000000 135.000000 149.000000 \n",
|
||
"50% 180.000000 147.000000 158.000000 217.000000 \n",
|
||
"75% 194.000000 173.000000 177.000000 239.000000 \n",
|
||
"max 253.000000 235.000000 244.000000 247.000000 \n",
|
||
"\n",
|
||
" left_block_S left_block_V left_block_l left_block_a \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 48.304482 180.058682 164.499669 140.003925 \n",
|
||
"std 19.148976 23.796653 28.073481 5.934290 \n",
|
||
"min 2.000000 78.000000 73.000000 97.000000 \n",
|
||
"25% 35.000000 165.000000 143.000000 136.000000 \n",
|
||
"50% 49.000000 181.000000 165.000000 142.000000 \n",
|
||
"75% 65.000000 196.000000 184.000000 145.000000 \n",
|
||
"max 206.000000 253.000000 241.000000 151.000000 \n",
|
||
"\n",
|
||
" left_block_b left_block_R_hist ... whiteBlock_b_hist \\\n",
|
||
"count 151086.000000 151086.000000 ... 151086.000000 \n",
|
||
"mean 127.971162 184.695405 ... 130.782197 \n",
|
||
"std 4.505780 23.740233 ... 4.662874 \n",
|
||
"min 105.000000 13.000000 ... 107.000000 \n",
|
||
"25% 127.000000 171.000000 ... 130.000000 \n",
|
||
"50% 128.000000 189.000000 ... 131.000000 \n",
|
||
"75% 130.000000 198.000000 ... 133.000000 \n",
|
||
"max 150.000000 254.000000 ... 150.000000 \n",
|
||
"\n",
|
||
" whiteBlock_R_max whiteBlock_G_max whiteBlock_B_max whiteBlock_H_max \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 202.084376 192.246787 189.165853 85.140000 \n",
|
||
"std 19.940399 21.283803 21.176846 98.779586 \n",
|
||
"min 125.000000 116.000000 107.000000 0.000000 \n",
|
||
"25% 193.000000 182.000000 179.000000 19.000000 \n",
|
||
"50% 205.000000 196.000000 193.000000 27.000000 \n",
|
||
"75% 212.000000 204.000000 201.000000 199.000000 \n",
|
||
"max 255.000000 255.000000 255.000000 255.000000 \n",
|
||
"\n",
|
||
" whiteBlock_S_max whiteBlock_V_max whiteBlock_l_max whiteBlock_a_max \\\n",
|
||
"count 151086.000000 151086.000000 151086.000000 151086.000000 \n",
|
||
"mean 25.093086 203.718994 200.058430 132.367804 \n",
|
||
"std 11.144240 18.427383 19.261219 2.745161 \n",
|
||
"min 0.000000 125.000000 125.000000 127.000000 \n",
|
||
"25% 17.000000 197.000000 190.000000 130.000000 \n",
|
||
"50% 22.000000 205.000000 203.000000 132.000000 \n",
|
||
"75% 32.000000 212.000000 210.000000 134.000000 \n",
|
||
"max 123.000000 255.000000 255.000000 158.000000 \n",
|
||
"\n",
|
||
" whiteBlock_b_max \n",
|
||
"count 151086.000000 \n",
|
||
"mean 131.734747 \n",
|
||
"std 4.569725 \n",
|
||
"min 108.000000 \n",
|
||
"25% 131.000000 \n",
|
||
"50% 132.000000 \n",
|
||
"75% 134.000000 \n",
|
||
"max 153.000000 \n",
|
||
"\n",
|
||
"[8 rows x 81 columns]"
|
||
]
|
||
},
|
||
"execution_count": 15,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"train_features.describe()"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"#from sklearn.model_selection import KFold\n",
|
||
"from sklearn.ensemble import RandomForestClassifier\n",
|
||
"from sklearn.metrics import accuracy_score\n",
|
||
"from sklearn.svm import SVC\n",
|
||
"from sklearn.metrics import f1_score\n",
|
||
"from sklearn.metrics import precision_score\n",
|
||
"from sklearn.metrics import recall_score\n",
|
||
"\n",
|
||
"\n",
|
||
"from sklearn.ensemble import ExtraTreesClassifier\n",
|
||
"from sklearn.ensemble import AdaBoostClassifier\n",
|
||
"\n",
|
||
"from sklearn.cross_validation import train_test_split\n",
|
||
"X_train ,X_test,y_train,y_test = train_test_split(train_features_9,train_labels,test_size = 0.2, random_state = 20)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 15,
|
||
"metadata": {
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"KFold(n_splits=5, random_state=None, shuffle=False)\n",
|
||
"('TRAIN:', array([ 21967, 21968, 21969, ..., 109831, 109832, 109833]), 'TEST:', array([ 0, 1, 2, ..., 21964, 21965, 21966]))\n",
|
||
"svm linear accuracy score: 0.99995447717\n",
|
||
"f1 score: 0.99995447717\n",
|
||
"runing time: 0:00:09.607839\n",
|
||
"('TRAIN:', array([ 0, 1, 2, ..., 109831, 109832, 109833]), 'TEST:', array([21967, 21968, 21969, ..., 43931, 43932, 43933]))\n",
|
||
"svm linear accuracy score: 1.0\n",
|
||
"f1 score: 1.0\n",
|
||
"runing time: 0:00:08.782720\n",
|
||
"('TRAIN:', array([ 0, 1, 2, ..., 109831, 109832, 109833]), 'TEST:', array([43934, 43935, 43936, ..., 65898, 65899, 65900]))\n",
|
||
"svm linear accuracy score: 0.999817908681\n",
|
||
"f1 score: 0.999817908681\n",
|
||
"runing time: 0:00:07.788273\n",
|
||
"('TRAIN:', array([ 0, 1, 2, ..., 109831, 109832, 109833]), 'TEST:', array([65901, 65902, 65903, ..., 87865, 87866, 87867]))\n",
|
||
"svm linear accuracy score: 0.999863431511\n",
|
||
"f1 score: 0.999863431511\n",
|
||
"runing time: 0:00:07.821979\n",
|
||
"('TRAIN:', array([ 0, 1, 2, ..., 87865, 87866, 87867]), 'TEST:', array([ 87868, 87869, 87870, ..., 109831, 109832, 109833]))\n",
|
||
"svm linear accuracy score: 0.999908950196\n",
|
||
"f1 score: 0.999908950196\n",
|
||
"runing time: 0:00:08.742652\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"\n",
|
||
"X = train_features.values\n",
|
||
"y = train_labels.values\n",
|
||
"\n",
|
||
"kf = KFold(n_splits=5)\n",
|
||
"kf.get_n_splits(X)\n",
|
||
"\n",
|
||
"print(kf) \n",
|
||
"\n",
|
||
"for train_index, test_index in kf.split(X):\n",
|
||
" print(\"TRAIN:\", train_index, \"TEST:\", test_index)\n",
|
||
" X_train, X_test = X[train_index], X[test_index]\n",
|
||
" y_train, y_test = y[train_index], y[test_index]\n",
|
||
" \n",
|
||
" \n",
|
||
" from datetime import datetime\n",
|
||
" trarining_start_time = datetime.now()\n",
|
||
"\n",
|
||
" clf_svm_linear = SVC(kernel = 'linear',gamma=0.00001,C=0.1)\n",
|
||
" clf_svm_linear = clf_svm_linear.fit(X_train, y_train)\n",
|
||
" pred = clf_svm_linear.predict(X_test)\n",
|
||
" print \"svm linear accuracy score:\" , accuracy_score(y_test,pred)\n",
|
||
" print \"f1 score:\" , f1_score(y_test,pred,average='micro')\n",
|
||
"\n",
|
||
"\n",
|
||
" training_stop_time = datetime.now()\n",
|
||
"\n",
|
||
" print \"runing time:\",(training_stop_time - trarining_start_time)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"metadata": {
|
||
"collapsed": true,
|
||
"scrolled": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"#X_train = train_features_9\n",
|
||
"#y_train = train_labels\n",
|
||
"\n",
|
||
"# X_test = test_features\n",
|
||
"# y_test = test_labels\n",
|
||
"\n",
|
||
"#clf_svm_linear = SVC(kernel = 'linear',gamma=0.00001,C=0.01)\n",
|
||
"clf_svm_linear = SVC(kernel = 'linear',gamma=0.01,C=0.01)\n",
|
||
"\n",
|
||
"clf_svm_linear = clf_svm_linear.fit(X_train, y_train)\n",
|
||
"# pred = clf_svm_linear.predict(X_test)\n",
|
||
"# print \"svm linear accuracy score:\" , accuracy_score(y_test,pred)\n",
|
||
"# print \"f1 score:\" , f1_score(y_test,pred,average='micro')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"metadata": {
|
||
"scrolled": false
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"svm linear accuracy score: 0.999671430918\n",
|
||
"f1 score : [ 1. 0.99931554 0.99927693 1. 1. 0.99964577\n",
|
||
" 0.99963464]\n",
|
||
"precision_score: [ 1. 0.99965765 0.99891579 1. 1. 0.99929178\n",
|
||
" 1. ]\n",
|
||
"recall_score : [ 1. 0.99897366 0.99963834 1. 1. 1.\n",
|
||
" 0.99926954]\n",
|
||
"('preds:', array([6, 6, 1, 4, 2, 3, 5, 1, 4, 1]))\n",
|
||
"('trues:\\n', array([6, 6, 1, 4, 2, 3, 5, 1, 4, 1]))\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"pred = clf_svm_linear.predict(X_test)\n",
|
||
"print \"svm linear accuracy score:\" , accuracy_score(y_test,pred)\n",
|
||
"print \"f1 score :\" , f1_score(y_test,pred,average=None)\n",
|
||
"print \"precision_score:\" , precision_score(y_test,pred,average=None)\n",
|
||
"print \"recall_score :\" , recall_score(y_test,pred,average=None)\n",
|
||
"\n",
|
||
"print(\"preds:\",pred[:10])\n",
|
||
"print('trues:\\n',y_test[:10])\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 141,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn_porter import Porter\n",
|
||
"\n",
|
||
"porter_clf_svm_linear = Porter(clf_svm_linear, language='c').export()\n",
|
||
"#porter_clf_svm_poly = Porter(clf_svm_poly, language='c').export()\n",
|
||
"# porter_clf_forest = Porter(clf_randomForest, language='c').export()\n",
|
||
"#porter_clf_extra_forest = Porter(clf_extra_forest, language='c').export()\n",
|
||
"\n",
|
||
"#print(porter_clf_svm_linear)\n",
|
||
"f = open(\"clf/clf_svm_linear_50features_20171207.txt\",'wb')\n",
|
||
"#f = open(\"clf_svm_linear_125100_low_feature_data.txt\",'wb')\n",
|
||
"f.write(porter_clf_svm_linear)\n",
|
||
"f.close()\n",
|
||
"#f = open(\"clf_svm_poly_2457100_data.txt\",'wb')\n",
|
||
"#f.write(porter_clf_svm_poly)\n",
|
||
"#f.close()\n",
|
||
"# f = open(\"clf/clf_randomForest_27features_stddev_c_0_01.txt\",'wb')\n",
|
||
"# f.write(porter_clf_forest)\n",
|
||
"# f.close()\n",
|
||
"# f = open(\"oclf_extra_forest_2457100_data_0824.txt\",'wb')\n",
|
||
"# f.write(porter_clf_extra_forest)\n",
|
||
"# f.close()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"metadata": {
|
||
"scrolled": true
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"<div>\n",
|
||
"<style>\n",
|
||
" .dataframe thead tr:only-child th {\n",
|
||
" text-align: right;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe thead th {\n",
|
||
" text-align: left;\n",
|
||
" }\n",
|
||
"\n",
|
||
" .dataframe tbody tr th {\n",
|
||
" vertical-align: top;\n",
|
||
" }\n",
|
||
"</style>\n",
|
||
"<table border=\"1\" class=\"dataframe\">\n",
|
||
" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>lelf_right_R</th>\n",
|
||
" <th>lelf_right_G</th>\n",
|
||
" <th>lelf_right_B</th>\n",
|
||
" <th>lelf_right_H</th>\n",
|
||
" <th>lelf_right_V</th>\n",
|
||
" <th>lelf_right_l</th>\n",
|
||
" <th>lelf_right_a</th>\n",
|
||
" <th>lelf_right_b</th>\n",
|
||
" <th>lelf_right_R_stddev</th>\n",
|
||
" <th>lelf_right_G_stddev</th>\n",
|
||
" <th>...</th>\n",
|
||
" <th>lelf_right_H_min</th>\n",
|
||
" <th>lelf_right_V_min</th>\n",
|
||
" <th>lelf_right_l_min</th>\n",
|
||
" <th>lelf_right_a_min</th>\n",
|
||
" <th>lelf_right_b_min</th>\n",
|
||
" <th>lelf_right_gray_value</th>\n",
|
||
" <th>lelf_right_gray_stddev</th>\n",
|
||
" <th>lelf_right_gray_hist</th>\n",
|
||
" <th>lelf_right_gray_max</th>\n",
|
||
" <th>lelf_right_gray_min</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>count</th>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" <td>9472.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>mean</th>\n",
|
||
" <td>4.998839</td>\n",
|
||
" <td>14.260557</td>\n",
|
||
" <td>10.544130</td>\n",
|
||
" <td>-26.535051</td>\n",
|
||
" <td>5.136824</td>\n",
|
||
" <td>11.130912</td>\n",
|
||
" <td>-4.211888</td>\n",
|
||
" <td>0.506651</td>\n",
|
||
" <td>-0.101668</td>\n",
|
||
" <td>-2.332454</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>-24.483847</td>\n",
|
||
" <td>0.697741</td>\n",
|
||
" <td>8.245777</td>\n",
|
||
" <td>-1.225190</td>\n",
|
||
" <td>0.677787</td>\n",
|
||
" <td>11.064189</td>\n",
|
||
" <td>-1.537901</td>\n",
|
||
" <td>25.800570</td>\n",
|
||
" <td>2.967166</td>\n",
|
||
" <td>8.171769</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>std</th>\n",
|
||
" <td>12.451409</td>\n",
|
||
" <td>22.429921</td>\n",
|
||
" <td>18.349035</td>\n",
|
||
" <td>54.743651</td>\n",
|
||
" <td>12.618626</td>\n",
|
||
" <td>18.760779</td>\n",
|
||
" <td>5.012831</td>\n",
|
||
" <td>1.030707</td>\n",
|
||
" <td>5.735642</td>\n",
|
||
" <td>8.606866</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>88.738964</td>\n",
|
||
" <td>20.699370</td>\n",
|
||
" <td>31.093443</td>\n",
|
||
" <td>2.420103</td>\n",
|
||
" <td>1.601545</td>\n",
|
||
" <td>18.888033</td>\n",
|
||
" <td>7.605926</td>\n",
|
||
" <td>26.195686</td>\n",
|
||
" <td>7.129989</td>\n",
|
||
" <td>31.073313</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>min</th>\n",
|
||
" <td>-18.000000</td>\n",
|
||
" <td>-23.000000</td>\n",
|
||
" <td>-22.000000</td>\n",
|
||
" <td>-243.000000</td>\n",
|
||
" <td>-18.000000</td>\n",
|
||
" <td>-21.000000</td>\n",
|
||
" <td>-16.000000</td>\n",
|
||
" <td>-4.000000</td>\n",
|
||
" <td>-15.000000</td>\n",
|
||
" <td>-22.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>-248.000000</td>\n",
|
||
" <td>-68.000000</td>\n",
|
||
" <td>-51.000000</td>\n",
|
||
" <td>-11.000000</td>\n",
|
||
" <td>-5.000000</td>\n",
|
||
" <td>-21.000000</td>\n",
|
||
" <td>-19.000000</td>\n",
|
||
" <td>-61.000000</td>\n",
|
||
" <td>-16.000000</td>\n",
|
||
" <td>-50.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25%</th>\n",
|
||
" <td>-6.000000</td>\n",
|
||
" <td>-6.000000</td>\n",
|
||
" <td>-7.000000</td>\n",
|
||
" <td>-28.000000</td>\n",
|
||
" <td>-6.000000</td>\n",
|
||
" <td>-6.000000</td>\n",
|
||
" <td>-7.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>-4.000000</td>\n",
|
||
" <td>-9.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>-3.000000</td>\n",
|
||
" <td>-5.000000</td>\n",
|
||
" <td>-20.000000</td>\n",
|
||
" <td>-3.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>-6.000000</td>\n",
|
||
" <td>-7.000000</td>\n",
|
||
" <td>12.000000</td>\n",
|
||
" <td>-3.000000</td>\n",
|
||
" <td>-20.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>50%</th>\n",
|
||
" <td>7.000000</td>\n",
|
||
" <td>16.000000</td>\n",
|
||
" <td>13.000000</td>\n",
|
||
" <td>-2.000000</td>\n",
|
||
" <td>7.000000</td>\n",
|
||
" <td>13.000000</td>\n",
|
||
" <td>-4.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>-1.000000</td>\n",
|
||
" <td>-3.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>2.000000</td>\n",
|
||
" <td>12.000000</td>\n",
|
||
" <td>-1.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>13.000000</td>\n",
|
||
" <td>-2.000000</td>\n",
|
||
" <td>28.000000</td>\n",
|
||
" <td>3.000000</td>\n",
|
||
" <td>12.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>75%</th>\n",
|
||
" <td>14.000000</td>\n",
|
||
" <td>27.000000</td>\n",
|
||
" <td>22.000000</td>\n",
|
||
" <td>3.000000</td>\n",
|
||
" <td>14.000000</td>\n",
|
||
" <td>23.000000</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>5.000000</td>\n",
|
||
" <td>6.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>2.000000</td>\n",
|
||
" <td>8.000000</td>\n",
|
||
" <td>30.000000</td>\n",
|
||
" <td>0.000000</td>\n",
|
||
" <td>1.000000</td>\n",
|
||
" <td>22.000000</td>\n",
|
||
" <td>5.000000</td>\n",
|
||
" <td>43.000000</td>\n",
|
||
" <td>8.000000</td>\n",
|
||
" <td>29.000000</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>max</th>\n",
|
||
" <td>38.000000</td>\n",
|
||
" <td>69.000000</td>\n",
|
||
" <td>56.000000</td>\n",
|
||
" <td>92.000000</td>\n",
|
||
" <td>38.000000</td>\n",
|
||
" <td>57.000000</td>\n",
|
||
" <td>7.000000</td>\n",
|
||
" <td>5.000000</td>\n",
|
||
" <td>12.000000</td>\n",
|
||
" <td>15.000000</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>241.000000</td>\n",
|
||
" <td>53.000000</td>\n",
|
||
" <td>73.000000</td>\n",
|
||
" <td>5.000000</td>\n",
|
||
" <td>7.000000</td>\n",
|
||
" <td>58.000000</td>\n",
|
||
" <td>14.000000</td>\n",
|
||
" <td>93.000000</td>\n",
|
||
" <td>26.000000</td>\n",
|
||
" <td>73.000000</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>8 rows × 45 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" lelf_right_R lelf_right_G lelf_right_B lelf_right_H lelf_right_V \\\n",
|
||
"count 9472.000000 9472.000000 9472.000000 9472.000000 9472.000000 \n",
|
||
"mean 4.998839 14.260557 10.544130 -26.535051 5.136824 \n",
|
||
"std 12.451409 22.429921 18.349035 54.743651 12.618626 \n",
|
||
"min -18.000000 -23.000000 -22.000000 -243.000000 -18.000000 \n",
|
||
"25% -6.000000 -6.000000 -7.000000 -28.000000 -6.000000 \n",
|
||
"50% 7.000000 16.000000 13.000000 -2.000000 7.000000 \n",
|
||
"75% 14.000000 27.000000 22.000000 3.000000 14.000000 \n",
|
||
"max 38.000000 69.000000 56.000000 92.000000 38.000000 \n",
|
||
"\n",
|
||
" lelf_right_l lelf_right_a lelf_right_b lelf_right_R_stddev \\\n",
|
||
"count 9472.000000 9472.000000 9472.000000 9472.000000 \n",
|
||
"mean 11.130912 -4.211888 0.506651 -0.101668 \n",
|
||
"std 18.760779 5.012831 1.030707 5.735642 \n",
|
||
"min -21.000000 -16.000000 -4.000000 -15.000000 \n",
|
||
"25% -6.000000 -7.000000 0.000000 -4.000000 \n",
|
||
"50% 13.000000 -4.000000 0.000000 -1.000000 \n",
|
||
"75% 23.000000 1.000000 1.000000 5.000000 \n",
|
||
"max 57.000000 7.000000 5.000000 12.000000 \n",
|
||
"\n",
|
||
" lelf_right_G_stddev ... lelf_right_H_min \\\n",
|
||
"count 9472.000000 ... 9472.000000 \n",
|
||
"mean -2.332454 ... -24.483847 \n",
|
||
"std 8.606866 ... 88.738964 \n",
|
||
"min -22.000000 ... -248.000000 \n",
|
||
"25% -9.000000 ... -3.000000 \n",
|
||
"50% -3.000000 ... 0.000000 \n",
|
||
"75% 6.000000 ... 2.000000 \n",
|
||
"max 15.000000 ... 241.000000 \n",
|
||
"\n",
|
||
" lelf_right_V_min lelf_right_l_min lelf_right_a_min lelf_right_b_min \\\n",
|
||
"count 9472.000000 9472.000000 9472.000000 9472.000000 \n",
|
||
"mean 0.697741 8.245777 -1.225190 0.677787 \n",
|
||
"std 20.699370 31.093443 2.420103 1.601545 \n",
|
||
"min -68.000000 -51.000000 -11.000000 -5.000000 \n",
|
||
"25% -5.000000 -20.000000 -3.000000 0.000000 \n",
|
||
"50% 2.000000 12.000000 -1.000000 0.000000 \n",
|
||
"75% 8.000000 30.000000 0.000000 1.000000 \n",
|
||
"max 53.000000 73.000000 5.000000 7.000000 \n",
|
||
"\n",
|
||
" lelf_right_gray_value lelf_right_gray_stddev lelf_right_gray_hist \\\n",
|
||
"count 9472.000000 9472.000000 9472.000000 \n",
|
||
"mean 11.064189 -1.537901 25.800570 \n",
|
||
"std 18.888033 7.605926 26.195686 \n",
|
||
"min -21.000000 -19.000000 -61.000000 \n",
|
||
"25% -6.000000 -7.000000 12.000000 \n",
|
||
"50% 13.000000 -2.000000 28.000000 \n",
|
||
"75% 22.000000 5.000000 43.000000 \n",
|
||
"max 58.000000 14.000000 93.000000 \n",
|
||
"\n",
|
||
" lelf_right_gray_max lelf_right_gray_min \n",
|
||
"count 9472.000000 9472.000000 \n",
|
||
"mean 2.967166 8.171769 \n",
|
||
"std 7.129989 31.073313 \n",
|
||
"min -16.000000 -50.000000 \n",
|
||
"25% -3.000000 -20.000000 \n",
|
||
"50% 3.000000 12.000000 \n",
|
||
"75% 8.000000 29.000000 \n",
|
||
"max 26.000000 73.000000 \n",
|
||
"\n",
|
||
"[8 rows x 45 columns]"
|
||
]
|
||
},
|
||
"execution_count": 10,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"from sklearn.utils import shuffle\n",
|
||
"\n",
|
||
"\n",
|
||
"# data_shuffle1 = shuffle(data1)\n",
|
||
"# #data_shuffle = data_all;\n",
|
||
"# test_labels = data_shuffle1[\"index\"]\n",
|
||
"# test_features = data_shuffle1.drop(\"dateTime\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"index\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"whiteBalance\",axis=1)\n",
|
||
"\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"left_block_R_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"left_block_G_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"left_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"left_block_H_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"left_block_S_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"left_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"left_block_l_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"left_block_a_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"left_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"right_block_R_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"right_block_G_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"right_block_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"right_block_H_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"right_block_S_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"right_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"right_block_l_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"right_block_a_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"right_block_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_R_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_G_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_B_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_H_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_S_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_l_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_a_stddev\",axis=1)\n",
|
||
"# test_features = test_features.drop(\"whiteBlock_b_stddev\",axis=1)\n",
|
||
"\n",
|
||
"train_features_10 = pd.DataFrame()\n",
|
||
"train_features_10['lelf_right_R'] = test_features['left_block_R'] - test_features['right_block_R']\n",
|
||
"train_features_10['lelf_right_G'] = test_features['left_block_G'] - test_features['right_block_G']\n",
|
||
"train_features_10['lelf_right_B'] = test_features['left_block_B'] - test_features['right_block_B']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_H'] = test_features['left_block_H'] - test_features['right_block_H']\n",
|
||
"# train_features_10['lelf_right_S'] = test_features['left_block_S'] - test_features['right_block_S']\n",
|
||
"train_features_10['lelf_right_V'] = test_features['left_block_V'] - test_features['right_block_V']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_l'] = test_features['left_block_l'] - test_features['right_block_l']\n",
|
||
"train_features_10['lelf_right_a'] = test_features['left_block_a'] - test_features['right_block_a']\n",
|
||
"train_features_10['lelf_right_b'] = test_features['left_block_b'] - test_features['right_block_b']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_R_stddev'] = test_features['left_block_R_stddev'] - test_features['right_block_R_stddev']\n",
|
||
"train_features_10['lelf_right_G_stddev'] = test_features['left_block_G_stddev'] - test_features['right_block_G_stddev']\n",
|
||
"train_features_10['lelf_right_B_stddev'] = test_features['left_block_B_stddev'] - test_features['right_block_B_stddev']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_H_stddev'] = test_features['left_block_H_stddev'] - test_features['right_block_H_stddev']\n",
|
||
"# train_features_10['lelf_right_S_stddev'] = test_features['left_block_S_stddev'] - test_features['right_block_S_stddev']\n",
|
||
"train_features_10['lelf_right_V_stddev'] = test_features['left_block_V_stddev'] - test_features['right_block_V_stddev']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_l_stddev'] = test_features['left_block_l_stddev'] - test_features['right_block_l_stddev']\n",
|
||
"train_features_10['lelf_right_a_stddev'] = test_features['left_block_a_stddev'] - test_features['right_block_a_stddev']\n",
|
||
"train_features_10['lelf_right_b_stddev'] = test_features['left_block_b_stddev'] - test_features['right_block_b_stddev']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_R_hist'] = test_features['left_block_R_hist'] - test_features['right_block_R_hist']\n",
|
||
"train_features_10['lelf_right_G_hist'] = test_features['left_block_G_hist'] - test_features['right_block_G_hist']\n",
|
||
"train_features_10['lelf_right_B_hist'] = test_features['left_block_B_hist'] - test_features['right_block_B_hist']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_H_hist'] = test_features['left_block_H_hist'] - test_features['right_block_H_hist']\n",
|
||
"# train_features_10['lelf_right_S_hist'] = test_features['left_block_S_hist'] - test_features['right_block_S_hist']\n",
|
||
"train_features_10['lelf_right_V_hist'] = test_features['left_block_V_hist'] - test_features['right_block_V_hist']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_l_hist'] = test_features['left_block_l_hist'] - test_features['right_block_l_hist']\n",
|
||
"train_features_10['lelf_right_a_hist'] = test_features['left_block_a_hist'] - test_features['right_block_a_hist']\n",
|
||
"train_features_10['lelf_right_b_hist'] = test_features['left_block_b_hist'] - test_features['right_block_b_hist']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_R_max'] = test_features['left_block_R_max'] - test_features['right_block_R_max']\n",
|
||
"train_features_10['lelf_right_G_max'] = test_features['left_block_G_max'] - test_features['right_block_G_max']\n",
|
||
"train_features_10['lelf_right_B_max'] = test_features['left_block_B_max'] - test_features['right_block_B_max']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_H_max'] = test_features['left_block_H_max'] - test_features['right_block_H_max']\n",
|
||
"# train_features_10['lelf_right_S_max'] = test_features['left_block_S_max'] - test_features['right_block_S_max']\n",
|
||
"train_features_10['lelf_right_V_max'] = test_features['left_block_V_max'] - test_features['right_block_V_max']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_l_max'] = test_features['left_block_l_max'] - test_features['right_block_l_max']\n",
|
||
"train_features_10['lelf_right_a_max'] = test_features['left_block_a_max'] - test_features['right_block_a_max']\n",
|
||
"train_features_10['lelf_right_b_max'] = test_features['left_block_b_max'] - test_features['right_block_b_max']\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_R_min'] = test_features['left_block_R_min'] - test_features['right_block_R_min']\n",
|
||
"train_features_10['lelf_right_G_min'] = test_features['left_block_G_min'] - test_features['right_block_G_min']\n",
|
||
"train_features_10['lelf_right_B_min'] = test_features['left_block_B_min'] - test_features['right_block_B_min']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_H_min'] = test_features['left_block_H_min'] - test_features['right_block_H_min']\n",
|
||
"# train_features_10['lelf_right_S_min'] = test_features['left_block_S_min'] - test_features['right_block_S_min']\n",
|
||
"train_features_10['lelf_right_V_min'] = test_features['left_block_V_min'] - test_features['right_block_V_min']\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_l_min'] = test_features['left_block_l_min'] - test_features['right_block_l_min']\n",
|
||
"train_features_10['lelf_right_a_min'] = test_features['left_block_a_min'] - test_features['right_block_a_min']\n",
|
||
"train_features_10['lelf_right_b_min'] = test_features['left_block_b_min'] - test_features['right_block_b_min']\n",
|
||
"\n",
|
||
"# train_features_10['left_grayValue']= test_features['left_grayValue'];\n",
|
||
"# train_features_10['left_grayStddevValue']= test_features['left_grayStddevValue'];\n",
|
||
"# train_features_10['left_grayHist']= test_features['left_grayHist'];\n",
|
||
"# train_features_10['left_grayMax']= test_features['left_grayMax'];\n",
|
||
"# train_features_10['left_grayMin']= test_features['left_grayMin'];\n",
|
||
"\n",
|
||
"# train_features_10['right_grayValue']= test_features['right_grayValue'];\n",
|
||
"# train_features_10['right_grayStddevValue']= test_features['right_grayStddevValue'];\n",
|
||
"# train_features_10['right_grayHist']= test_features['right_grayHist'];\n",
|
||
"# train_features_10['right_grayMax']= test_features['right_grayMax'];\n",
|
||
"# train_features_10['right_grayMin']= test_features['right_grayMin'];\n",
|
||
"\n",
|
||
"# train_features_10['lelf_R_stddev'] = test_features['left_block_R_stddev'] \n",
|
||
"# train_features_10['lelf_G_stddev'] = test_features['left_block_G_stddev'] \n",
|
||
"# train_features_10['lelf_B_stddev'] = test_features['left_block_B_stddev'] \n",
|
||
"\n",
|
||
"# train_features_10['left_block_R_min'] = test_features['left_block_R_min'] \n",
|
||
"# train_features_10['left_block_G_min'] = test_features['left_block_G_min'] \n",
|
||
"# train_features_10['left_block_B_min'] = test_features['left_block_B_min'] \n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"train_features_10['lelf_right_gray_value'] = test_features['left_grayValue'] - test_features['right_grayValue']\n",
|
||
"train_features_10['lelf_right_gray_stddev'] = test_features['left_grayStddevValue'] - test_features['right_grayStddevValue']\n",
|
||
"train_features_10['lelf_right_gray_hist'] = test_features['left_grayHist'] - test_features['right_grayHist']\n",
|
||
"train_features_10['lelf_right_gray_max'] = test_features['left_grayMax'] - test_features['right_grayMax']\n",
|
||
"train_features_10['lelf_right_gray_min'] = test_features['left_grayMin'] - test_features['right_grayMin']\n",
|
||
"\n",
|
||
"train_features_10.describe()\n",
|
||
"\n",
|
||
"\n",
|
||
"# feature = feature.drop(\"left_block_H_hist\",axis=1)\n",
|
||
"# feature = feature.drop(\"right_block_H_hist\",axis=1)\n",
|
||
"# feature = feature.drop(\"whiteBlock_H_hist\",axis=1)\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 111,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
" \n",
|
||
"test_features = test_features.drop(\"left_block_H\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_S\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_V\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"right_block_H\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_S\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_V\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"whiteBlock_H\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_S\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_V\",axis=1)\n",
|
||
"\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"left_block_H_stddev\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_S_stddev\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"right_block_H_stddev\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_S_stddev\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"whiteBlock_H_stddev\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_S_stddev\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_V_stddev\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"left_block_H_hist\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_S_hist\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"right_block_H_hist\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_S_hist\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"whiteBlock_H_hist\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_S_hist\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_V_hist\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"left_block_H_max\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_S_max\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"right_block_H_max\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_S_max\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_V_max\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"whiteBlock_H_max\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_S_max\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_V_max\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"left_block_H_min\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_S_min\",axis=1)\n",
|
||
"test_features = test_features.drop(\"left_block_V_min\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"right_block_H_min\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_S_min\",axis=1)\n",
|
||
"test_features = test_features.drop(\"right_block_V_min\",axis=1)\n",
|
||
"\n",
|
||
"test_features = test_features.drop(\"whiteBlock_H_min\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_S_min\",axis=1)\n",
|
||
"test_features = test_features.drop(\"whiteBlock_V_min\",axis=1)\n",
|
||
" \n",
|
||
" \n",
|
||
"test_features['lelf_right_R'] = test_features['left_block_R'] - test_features['right_block_R']\n",
|
||
"test_features['lelf_right_G'] = test_features['left_block_G'] - test_features['right_block_G']\n",
|
||
"test_features['lelf_right_B'] = test_features['left_block_B'] - test_features['right_block_B']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_H'] = test_features['left_block_H'] - test_features['right_block_H']\n",
|
||
"# test_features['lelf_right_S'] = test_features['left_block_S'] - test_features['right_block_S']\n",
|
||
"# test_features['lelf_right_V'] = test_features['left_block_V'] - test_features['right_block_V']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_l'] = test_features['left_block_l'] - test_features['right_block_l']\n",
|
||
"# test_features['lelf_right_a'] = test_features['left_block_a'] - test_features['right_block_a']\n",
|
||
"# test_features['lelf_right_b'] = test_features['left_block_b'] - test_features['right_block_b']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_R_stddev'] = test_features['left_block_R_stddev'] - test_features['right_block_R_stddev']\n",
|
||
"# test_features['lelf_right_G_stddev'] = test_features['left_block_G_stddev'] - test_features['right_block_G_stddev']\n",
|
||
"# test_features['lelf_right_B_stddev'] = test_features['left_block_B_stddev'] - test_features['right_block_B_stddev']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_H_stddev'] = test_features['left_block_H_stddev'] - test_features['right_block_H_stddev']\n",
|
||
"# test_features['lelf_right_S_stddev'] = test_features['left_block_S_stddev'] - test_features['right_block_S_stddev']\n",
|
||
"# test_features['lelf_right_V_stddev'] = test_features['left_block_V_stddev'] - test_features['right_block_V_stddev']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_l_stddev'] = test_features['left_block_l_stddev'] - test_features['right_block_l_stddev']\n",
|
||
"# test_features['lelf_right_a_stddev'] = test_features['left_block_a_stddev'] - test_features['right_block_a_stddev']\n",
|
||
"# test_features['lelf_right_b_stddev'] = test_features['left_block_b_stddev'] - test_features['right_block_b_stddev']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_R_hist'] = test_features['left_block_R_hist'] - test_features['right_block_R_hist']\n",
|
||
"# test_features['lelf_right_G_hist'] = test_features['left_block_G_hist'] - test_features['right_block_G_hist']\n",
|
||
"# test_features['lelf_right_B_hist'] = test_features['left_block_B_hist'] - test_features['right_block_B_hist']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_H_hist'] = test_features['left_block_H_hist'] - test_features['right_block_H_hist']\n",
|
||
"# test_features['lelf_right_S_hist'] = test_features['left_block_S_hist'] - test_features['right_block_S_hist']\n",
|
||
"# test_features['lelf_right_V_hist'] = test_features['left_block_V_hist'] - test_features['right_block_V_hist']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_l_hist'] = test_features['left_block_l_hist'] - test_features['right_block_l_hist']\n",
|
||
"# test_features['lelf_right_a_hist'] = test_features['left_block_a_hist'] - test_features['right_block_a_hist']\n",
|
||
"# test_features['lelf_right_b_hist'] = test_features['left_block_b_hist'] - test_features['right_block_b_hist']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_R_max'] = test_features['left_block_R_max'] - test_features['right_block_R_max']\n",
|
||
"# test_features['lelf_right_G_max'] = test_features['left_block_G_max'] - test_features['right_block_G_max']\n",
|
||
"# test_features['lelf_right_B_max'] = test_features['left_block_B_max'] - test_features['right_block_B_max']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_H_max'] = test_features['left_block_H_max'] - test_features['right_block_H_max']\n",
|
||
"# test_features['lelf_right_S_max'] = test_features['left_block_S_max'] - test_features['right_block_S_max']\n",
|
||
"# test_features['lelf_right_V_max'] = test_features['left_block_V_max'] - test_features['right_block_V_max']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_l_max'] = test_features['left_block_l_max'] - test_features['right_block_l_max']\n",
|
||
"# test_features['lelf_right_a_max'] = test_features['left_block_a_max'] - test_features['right_block_a_max']\n",
|
||
"# test_features['lelf_right_b_max'] = test_features['left_block_b_max'] - test_features['right_block_b_max']\n",
|
||
"\n",
|
||
"\n",
|
||
"\n",
|
||
"# test_features['lelf_right_R_min'] = test_features['left_block_R_min'] - test_features['right_block_R_min']\n",
|
||
"# test_features['lelf_right_G_min'] = test_features['left_block_G_min'] - test_features['right_block_G_min']\n",
|
||
"# test_features['lelf_right_B_min'] = test_features['left_block_B_min'] - test_features['right_block_B_min']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_H_min'] = test_features['left_block_H_min'] - test_features['right_block_H_min']\n",
|
||
"# test_features['lelf_right_S_min'] = test_features['left_block_S_min'] - test_features['right_block_S_min']\n",
|
||
"# test_features['lelf_right_V_min'] = test_features['left_block_V_min'] - test_features['right_block_V_min']\n",
|
||
"\n",
|
||
"# test_features['lelf_right_l_min'] = test_features['left_block_l_min'] - test_features['right_block_l_min']\n",
|
||
"# test_features['lelf_right_a_min'] = test_features['left_block_a_min'] - test_features['right_block_a_min']\n",
|
||
"# test_features['lelf_right_b_min'] = test_features['left_block_b_min'] - test_features['right_block_b_min']\n",
|
||
"\n",
|
||
"test_features['lelf_right_gray_value'] = test_features['left_grayValue'] - test_features['right_grayValue']\n",
|
||
"test_features['lelf_right_gray_stddev'] = test_features['left_grayStddevValue'] - test_features['right_grayStddevValue']\n",
|
||
"test_features['lelf_right_gray_hist'] = test_features['left_grayHist'] - test_features['right_grayHist']\n",
|
||
"test_features['lelf_right_gray_max'] = test_features['left_grayMax'] - test_features['right_grayMax']\n",
|
||
"test_features['lelf_right_gray_min'] = test_features['left_grayMin'] - test_features['right_grayMin']\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 14,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"svm linear accuracy score: 0.868243243243\n",
|
||
"f1 score: 0.868243243243\n",
|
||
"recall_score : 0.868243243243\n",
|
||
"precision_score : 0.868243243243\n",
|
||
"svm linear accuracy score: 0.907728040541\n",
|
||
"f1 score: 0.907728040541\n",
|
||
"recall_score : 0.907728040541\n",
|
||
"precision_score : 0.907728040541\n",
|
||
"('preds:', array([6, 1, 1, 6, 7, 7, 4, 4, 4, 4]))\n",
|
||
"('trues:\\n', 2720 6\n",
|
||
"3210 1\n",
|
||
"3118 1\n",
|
||
"2969 6\n",
|
||
"1026 7\n",
|
||
"1020 7\n",
|
||
"2258 4\n",
|
||
"2493 4\n",
|
||
"3424 4\n",
|
||
"2034 4\n",
|
||
"Name: index, dtype: int64)\n",
|
||
"7\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(6, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(6, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(6, 4)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 6)\n",
|
||
"(6, 4)\n",
|
||
"(6, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(6, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(9472, 2911, 118)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(0, 1)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(6, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 1)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(6, 7)\n",
|
||
"(4, 2)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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||
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||
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||
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||
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||
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||
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||
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||
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||
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|
||
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||
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|
||
"(7, 6)\n",
|
||
"(6, 7)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 1)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(6, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(6, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(6, 7)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 1)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(6, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(0, 1)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(6, 7)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 4)\n",
|
||
"(0, 1)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(2, 1)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(4, 2)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(7, 6)\n",
|
||
"(9472, 0, 874)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"pred = clf_svm_linear.predict(train_features_10)\n",
|
||
"test_features_gray_stddev = test_features['left_grayStddevValue']\n",
|
||
"test_features_np = np.ndarray(test_features_gray_stddev.shape,dtype = np.float32)\n",
|
||
"\n",
|
||
"test_features_np = test_features_gray_stddev.values\n",
|
||
"print \"svm linear accuracy score:\" , accuracy_score(test_labels,pred)\n",
|
||
"print \"f1 score:\" , f1_score(test_labels,pred,average='micro')\n",
|
||
"print \"recall_score :\" , recall_score(test_labels,pred,average='micro')\n",
|
||
"print \"precision_score :\" , precision_score(test_labels,pred,average='micro')\n",
|
||
"\n",
|
||
"for i in range(0, len(test_features_np)):\n",
|
||
" if test_features_np[i] < 3:\n",
|
||
" pred[i] =0\n",
|
||
"print \"svm linear accuracy score:\" , accuracy_score(test_labels,pred)\n",
|
||
"print \"f1 score:\" , f1_score(test_labels,pred,average='micro')\n",
|
||
"print \"recall_score :\" , recall_score(test_labels,pred,average='micro')\n",
|
||
"print \"precision_score :\" , precision_score(test_labels,pred,average='micro')\n",
|
||
"\n",
|
||
"\n",
|
||
"print(\"preds:\",pred[120:130])\n",
|
||
"print('trues:\\n',test_labels[120:130])\n",
|
||
"test_labels_np = np.ndarray(test_labels.shape,dtype= np.int32)\n",
|
||
"test_labels_np = test_labels.values\n",
|
||
"print(test_labels_np[0])\n",
|
||
"all_counter = 0\n",
|
||
"counter = 0\n",
|
||
"for i in range(0 ,len(pred) ):\n",
|
||
" if (pred[i] == 4 or (pred[i] == 4 and test_labels_np[i] ==4 )or test_labels_np[i] ==4 ) :\n",
|
||
" all_counter = all_counter + 1\n",
|
||
" if pred[i] != test_labels_np[i] :\n",
|
||
" counter = counter+1\n",
|
||
" print(pred[i] , test_labels_np[i])\n",
|
||
"print(len(pred),all_counter, counter) \n",
|
||
"all_counter = 0\n",
|
||
"counter = 0\n",
|
||
"for i in range(0 ,len(pred) ):\n",
|
||
" if pred[i] != test_labels_np[i] :\n",
|
||
" counter = counter+1\n",
|
||
" print(pred[i] , test_labels_np[i])\n",
|
||
"print(len(pred),all_counter, counter) \n",
|
||
"\n",
|
||
"# print \"svm linear accuracy score:\" , accuracy_score(test_labels,pred)\n",
|
||
"# print \"f1 score:\" , f1_score(test_labels,pred,average='micro')\n",
|
||
"# print \"recall_score :\" , recall_score(test_labels,pred,average='micro')\n",
|
||
"# print \"precision_score :\" , precision_score(test_labels,pred,average='micro')\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## from sklearn.metrics import recall_score\n",
|
||
"from sklearn.metrics import precision_score\n",
|
||
"print \"accuracy score:\" , accuracy_score(y_test,pred)\n",
|
||
"print \"recall_score :\" , recall_score(y_test,pred,average='macro')\n",
|
||
"print \"precision_score :\" , precision_score(y_test,pred,average='macro')\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 38,
|
||
"metadata": {
|
||
"collapsed": true
|
||
},
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn_porter import Porter\n",
|
||
"\n",
|
||
"porter_java = Porter(clf_svm, language='java').export()\n",
|
||
"porter_c = Porter(clf_svm, language='c').export()\n",
|
||
"\n",
|
||
"f = open(\"Protein_c.txt\",'wb')\n",
|
||
"f.write(porter_c)\n",
|
||
"f.close()\n",
|
||
"\n",
|
||
"f = open(\"Protein_svm_java.txt\",'wb')\n",
|
||
"f.write(porter_java)\n",
|
||
"f.close()"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.6.2"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|