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yola/zaoYun/master/clf/clf_svm_linear_bld.c
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2026-07-03 16:29:47 +08:00

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#include <stdlib.h>
#include <stdio.h>
#include <math.h>
#define N_FEATURES 6
#define N_CLASSES 5
#define N_VECTORS 93
#define N_ROWS 5
#define N_COEFFICIENTS 4
#define N_INTERCEPTS 10
#define KERNEL_TYPE 'l'
#define KERNEL_GAMMA 0.02
#define KERNEL_COEF 0.0
#define KERNEL_DEGREE 3
double vectors[93][6] = {{17.0, 184.0, 180.0, 144.0, 143.0, 175.0}, {25.0, 196.0, 229.0, 207.0, 122.0, 200.0}, {17.0, 167.0, 190.0, 156.0, 140.0, 173.0}, {25.0, 159.0, 229.0, 210.0, 123.0, 188.0}, {18.0, 113.0, 228.0, 200.0, 134.0, 164.0}, {21.0, 161.0, 149.0, 133.0, 131.0, 167.0}, {21.0, 175.0, 204.0, 177.0, 131.0, 183.0}, {24.0, 137.0, 190.0, 179.0, 123.0, 173.0}, {37.0, 115.0, 103.0, 106.0, 115.0, 153.0}, {44.0, 101.0, 127.0, 128.0, 109.0, 152.0}, {40.0, 120.0, 103.0, 105.0, 113.0, 153.0}, {26.0, 123.0, 173.0, 169.0, 121.0, 167.0}, {26.0, 126.0, 168.0, 164.0, 121.0, 167.0}, {40.0, 83.0, 141.0, 144.0, 113.0, 150.0}, {78.0, 111.0, 81.0, 80.0, 111.0, 131.0}, {79.0, 97.0, 78.0, 79.0, 114.0, 130.0}, {68.0, 66.0, 111.0, 113.0, 114.0, 134.0}, {79.0, 96.0, 85.0, 85.0, 113.0, 131.0}, {79.0, 103.0, 86.0, 86.0, 112.0, 131.0}, {80.0, 101.0, 75.0, 75.0, 114.0, 130.0}, {80.0, 109.0, 75.0, 74.0, 113.0, 131.0}, {78.0, 99.0, 81.0, 81.0, 113.0, 131.0}, {80.0, 105.0, 82.0, 82.0, 112.0, 130.0}, {78.0, 113.0, 78.0, 77.0, 111.0, 131.0}, {78.0, 101.0, 78.0, 78.0, 113.0, 131.0}, {78.0, 109.0, 73.0, 72.0, 113.0, 131.0}, {76.0, 78.0, 108.0, 109.0, 112.0, 132.0}, {79.0, 105.0, 77.0, 77.0, 113.0, 131.0}, {79.0, 110.0, 74.0, 73.0, 113.0, 130.0}, {78.0, 101.0, 80.0, 80.0, 113.0, 131.0}, {76.0, 92.0, 144.0, 142.0, 105.0, 134.0}, {79.0, 110.0, 76.0, 75.0, 112.0, 131.0}, {48.0, 94.0, 124.0, 125.0, 109.0, 150.0}, {80.0, 100.0, 75.0, 75.0, 114.0, 130.0}, {63.0, 88.0, 65.0, 64.0, 114.0, 137.0}, {78.0, 110.0, 68.0, 67.0, 113.0, 132.0}, {77.0, 112.0, 72.0, 71.0, 112.0, 132.0}, {80.0, 109.0, 75.0, 75.0, 113.0, 130.0}, {79.0, 115.0, 66.0, 65.0, 113.0, 130.0}, {78.0, 97.0, 80.0, 80.0, 113.0, 131.0}, {76.0, 100.0, 77.0, 77.0, 113.0, 132.0}, {78.0, 91.0, 126.0, 125.0, 108.0, 133.0}, {79.0, 103.0, 74.0, 74.0, 114.0, 130.0}, {79.0, 109.0, 69.0, 69.0, 114.0, 130.0}, {79.0, 98.0, 78.0, 78.0, 113.0, 130.0}, {79.0, 107.0, 75.0, 75.0, 113.0, 130.0}, {76.0, 109.0, 72.0, 71.0, 112.0, 133.0}, {76.0, 95.0, 77.0, 77.0, 113.0, 132.0}, {80.0, 109.0, 74.0, 73.0, 113.0, 130.0}, {79.0, 106.0, 76.0, 75.0, 113.0, 130.0}, {79.0, 111.0, 70.0, 69.0, 113.0, 131.0}, {79.0, 106.0, 72.0, 72.0, 113.0, 130.0}, {62.0, 86.0, 66.0, 65.0, 114.0, 137.0}, {80.0, 105.0, 72.0, 72.0, 114.0, 130.0}, {78.0, 111.0, 68.0, 67.0, 113.0, 132.0}, {76.0, 79.0, 100.0, 101.0, 113.0, 132.0}, {82.0, 112.0, 71.0, 71.0, 113.0, 129.0}, {78.0, 92.0, 99.0, 99.0, 111.0, 131.0}, {80.0, 85.0, 98.0, 99.0, 113.0, 130.0}, {79.0, 83.0, 94.0, 95.0, 114.0, 130.0}, {77.0, 108.0, 64.0, 63.0, 114.0, 131.0}, {78.0, 101.0, 66.0, 66.0, 115.0, 130.0}, {77.0, 76.0, 103.0, 104.0, 113.0, 131.0}, {77.0, 116.0, 62.0, 61.0, 113.0, 132.0}, {75.0, 95.0, 103.0, 103.0, 110.0, 134.0}, {77.0, 83.0, 100.0, 101.0, 112.0, 132.0}, {78.0, 128.0, 60.0, 58.0, 113.0, 131.0}, {77.0, 130.0, 57.0, 54.0, 112.0, 132.0}, {76.0, 104.0, 76.0, 76.0, 112.0, 132.0}, {79.0, 108.0, 63.0, 62.0, 114.0, 130.0}, {78.0, 105.0, 69.0, 68.0, 114.0, 131.0}, {78.0, 115.0, 64.0, 63.0, 114.0, 131.0}, {77.0, 113.0, 59.0, 58.0, 114.0, 131.0}, {78.0, 104.0, 66.0, 65.0, 114.0, 131.0}, {87.0, 149.0, 66.0, 65.0, 112.0, 126.0}, {75.0, 100.0, 61.0, 60.0, 115.0, 132.0}, {79.0, 80.0, 101.0, 102.0, 113.0, 130.0}, {82.0, 114.0, 67.0, 67.0, 114.0, 128.0}, {77.0, 108.0, 71.0, 70.0, 113.0, 131.0}, {77.0, 81.0, 103.0, 104.0, 112.0, 132.0}, {77.0, 101.0, 100.0, 100.0, 109.0, 133.0}, {76.0, 100.0, 88.0, 88.0, 111.0, 132.0}, {92.0, 140.0, 112.0, 107.0, 110.0, 119.0}, {78.0, 97.0, 77.0, 77.0, 114.0, 131.0}, {77.0, 107.0, 62.0, 61.0, 114.0, 131.0}, {76.0, 112.0, 82.0, 82.0, 110.0, 133.0}, {77.0, 114.0, 64.0, 62.0, 113.0, 132.0}, {78.0, 108.0, 66.0, 65.0, 114.0, 131.0}, {77.0, 122.0, 59.0, 57.0, 113.0, 131.0}, {78.0, 112.0, 63.0, 62.0, 114.0, 131.0}, {77.0, 107.0, 64.0, 63.0, 114.0, 131.0}, {79.0, 84.0, 100.0, 101.0, 113.0, 130.0}, {76.0, 95.0, 74.0, 74.0, 114.0, 132.0}};
double coefficients[4][93] = {{0.2565290311483519, 0.05267500339987255, 0.0, 0.20950627599236551, 0.0, -0.0, -0.5187103105405902, -0.0, -0.0, -0.0, -0.0, -0.0010448527083486035, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -6.109361749511185e-05, -0.0, -9.426169850730758e-05, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.00011249226615670169, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0}, {0.0, 0.0, 0.0006409460029816403, 0.0, 0.00040390670536696286, 0.0011432982690014588, 0.0, 0.0030922984943534404, -0.0, -0.0, -0.0, -0.0011043550586939232, -0.0031312417046609723, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0003006875411720932, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -4.069716877917173e-05, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.00015614271544448882, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0}, {0.0, 0.0, 0.0001260324256496354, 0.0, 2.9322890352784018e-05, 0.0002757211950621471, 0.0, 2.4966346109946043e-05, 0.0023995095618217694, 0.0184414720268768, 0.0, 0.0, 0.0, 0.0033456629645900147, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.02418664455328858, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0009819061623307815, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -2.720436339513482e-05, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0, -0.0}, {0.00011249226615670169, 0.0, 0.0, 0.0, 0.0, 0.00019683988422366055, 0.0, 0.0, 0.0, 0.0003956772868514533, 0.0006134332388744629, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2123274765620007, 1.0, 1.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.074040885622322, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.430480712493657, 1.0, 1.0, 1.0, 1.0, 0.5190837451319507, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -0.8416583147905249, -0.3942745050194007, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -0.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0, -1.0}};
double intercepts[10] = {-200.28236685326544, -12.722698747576993, -4.683435298339523, -3.3768490916249503, -23.40674493392091, -5.442900557586231, -3.5410727265396282, -34.786982466028775, -4.81798714325947, 39.73211471522999};
int weights[5] = {5, 3, 6, 41, 38};
int predict (double features[]) {
int i, j, k, d, l;
double kernels[N_VECTORS];
double kernel;
switch (KERNEL_TYPE) {
case 'l':
// <x,x'>
for (i = 0; i < N_VECTORS; i++) {
kernel = 0.;
for (j = 0; j < N_FEATURES; j++) {
kernel += vectors[i][j] * features[j];
}
kernels[i] = kernel;
}
break;
case 'p':
// (y<x,x'>+r)^d
for (i = 0; i < N_VECTORS; i++) {
kernel = 0.;
for (j = 0; j < N_FEATURES; j++) {
kernel += vectors[i][j] * features[j];
}
kernels[i] = pow((KERNEL_GAMMA * kernel) + KERNEL_COEF, KERNEL_DEGREE);
}
break;
case 'r':
// exp(-y|x-x'|^2)
for (i = 0; i < N_VECTORS; i++) {
kernel = 0.;
for (j = 0; j < N_FEATURES; j++) {
kernel += pow(vectors[i][j] - features[j], 2);
}
kernels[i] = exp(-KERNEL_GAMMA * kernel);
}
break;
case 's':
// tanh(y<x,x'>+r)
for (i = 0; i < N_VECTORS; i++) {
kernel = 0.;
for (j = 0; j < N_FEATURES; j++) {
kernel += vectors[i][j] * features[j];
}
kernels[i] = tanh((KERNEL_GAMMA * kernel) + KERNEL_COEF);
}
break;
}
int starts[N_ROWS];
int start;
for (i = 0; i < N_ROWS; i++) {
if (i != 0) {
start = 0;
for (j = 0; j < i; j++) {
start += weights[j];
}
starts[i] = start;
} else {
starts[0] = 0;
}
}
int ends[N_ROWS];
for (i = 0; i < N_ROWS; i++) {
ends[i] = weights[i] + starts[i];
}
if (N_CLASSES == 2) {
for (i = 0; i < N_VECTORS; i++) {
kernels[i] = -kernels[i];
}
double decision = 0.;
for (k = starts[1]; k < ends[1]; k++) {
decision += kernels[k] * coefficients[0][k];
}
for (k = starts[0]; k < ends[0]; k++) {
decision += kernels[k] * coefficients[0][k];
}
decision += intercepts[0];
if (decision > 0) {
return 0;
}
return 1;
}
double decisions[N_INTERCEPTS];
double tmp;
for (i = 0, d = 0, l = N_ROWS; i < l; i++) {
for (j = i + 1; j < l; j++) {
tmp = 0.;
for (k = starts[j]; k < ends[j]; k++) {
tmp += kernels[k] * coefficients[i][k];
}
for (k = starts[i]; k < ends[i]; k++) {
tmp += kernels[k] * coefficients[j - 1][k];
}
decisions[d] = tmp + intercepts[d];
d = d + 1;
}
}
int votes[N_INTERCEPTS];
for (i = 0, d = 0, l = N_ROWS; i < l; i++) {
for (j = i + 1; j < l; j++) {
votes[d] = decisions[d] > 0 ? i : j;
d = d + 1;
}
}
int amounts[N_CLASSES];
for (i = 0, l = N_CLASSES; i < l; i++) {
amounts[i] = 0;
}
for (i = 0; i < N_INTERCEPTS; i++) {
amounts[votes[i]] += 1;
}
int classVal = -1;
int classIdx = -1;
for (i = 0; i < N_CLASSES; i++) {
if (amounts[i] > classVal) {
classVal = amounts[i];
classIdx= i;
}
}
return classIdx;
}
int main(int argc, const char * argv[]) {
/* Features: */
double features[argc-1];
int i;
for (i = 1; i < argc; i++) {
features[i-1] = atof(argv[i]);
}
/* Prediction: */
printf("%d", predict(features));
return 0;
}
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