coco
153 lines
4.9 KiB
C++
153 lines
4.9 KiB
C++
// Copyright (C) 2011 Davis E. King (davis@dlib.net)
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// License: Boost Software License See LICENSE.txt for the full license.
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#ifndef DLIB_CROSS_VALIDATE_SEQUENCE_LABeLER_Hh_
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#define DLIB_CROSS_VALIDATE_SEQUENCE_LABeLER_Hh_
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#include "cross_validate_sequence_labeler_abstract.h"
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#include <vector>
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#include "../matrix.h"
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#include "svm.h"
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namespace dlib
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{
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// ----------------------------------------------------------------------------------------
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template <
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typename sequence_labeler_type,
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typename sequence_type
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>
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const matrix<double> test_sequence_labeler (
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const sequence_labeler_type& labeler,
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const std::vector<sequence_type>& samples,
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const std::vector<std::vector<unsigned long> >& labels
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)
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{
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// make sure requires clause is not broken
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DLIB_ASSERT( is_sequence_labeling_problem(samples, labels) == true,
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"\tmatrix test_sequence_labeler()"
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<< "\n\t invalid inputs were given to this function"
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<< "\n\t is_sequence_labeling_problem(samples, labels): "
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<< is_sequence_labeling_problem(samples, labels));
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matrix<double> res(labeler.num_labels(), labeler.num_labels());
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res = 0;
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std::vector<unsigned long> pred;
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for (unsigned long i = 0; i < samples.size(); ++i)
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{
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labeler.label_sequence(samples[i], pred);
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for (unsigned long j = 0; j < pred.size(); ++j)
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{
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const unsigned long truth = labels[i][j];
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if (truth >= static_cast<unsigned long>(res.nr()))
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{
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// ignore labels the labeler doesn't know about.
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continue;
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}
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res(truth, pred[j]) += 1;
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}
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}
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return res;
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}
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// ----------------------------------------------------------------------------------------
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template <
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typename trainer_type,
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typename sequence_type
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>
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const matrix<double> cross_validate_sequence_labeler (
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const trainer_type& trainer,
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const std::vector<sequence_type>& samples,
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const std::vector<std::vector<unsigned long> >& labels,
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const long folds
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)
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{
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// make sure requires clause is not broken
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DLIB_ASSERT(is_sequence_labeling_problem(samples,labels) == true &&
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1 < folds && folds <= static_cast<long>(samples.size()),
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"\tmatrix cross_validate_sequence_labeler()"
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<< "\n\t invalid inputs were given to this function"
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<< "\n\t samples.size(): " << samples.size()
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<< "\n\t folds: " << folds
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<< "\n\t is_sequence_labeling_problem(samples,labels): " << is_sequence_labeling_problem(samples,labels)
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);
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#ifdef ENABLE_ASSERTS
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for (unsigned long i = 0; i < labels.size(); ++i)
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{
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for (unsigned long j = 0; j < labels[i].size(); ++j)
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{
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// make sure requires clause is not broken
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DLIB_ASSERT(labels[i][j] < trainer.num_labels(),
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"\t matrix cross_validate_sequence_labeler()"
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<< "\n\t The labels are invalid."
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<< "\n\t labels[i][j]: " << labels[i][j]
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<< "\n\t trainer.num_labels(): " << trainer.num_labels()
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<< "\n\t i: " << i
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<< "\n\t j: " << j
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);
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}
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}
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#endif
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const long num_in_test = samples.size()/folds;
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const long num_in_train = samples.size() - num_in_test;
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std::vector<sequence_type> x_test, x_train;
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std::vector<std::vector<unsigned long> > y_test, y_train;
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long next_test_idx = 0;
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matrix<double> res;
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for (long i = 0; i < folds; ++i)
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{
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x_test.clear();
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y_test.clear();
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x_train.clear();
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y_train.clear();
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// load up the test samples
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for (long cnt = 0; cnt < num_in_test; ++cnt)
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{
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x_test.push_back(samples[next_test_idx]);
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y_test.push_back(labels[next_test_idx]);
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next_test_idx = (next_test_idx + 1)%samples.size();
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}
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// load up the training samples
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long next = next_test_idx;
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for (long cnt = 0; cnt < num_in_train; ++cnt)
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{
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x_train.push_back(samples[next]);
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y_train.push_back(labels[next]);
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next = (next + 1)%samples.size();
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}
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res += test_sequence_labeler(trainer.train(x_train,y_train), x_test, y_test);
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} // for (long i = 0; i < folds; ++i)
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return res;
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}
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// ----------------------------------------------------------------------------------------
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}
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#endif // DLIB_CROSS_VALIDATE_SEQUENCE_LABeLER_Hh_
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