summaryrefslogtreecommitdiffstats
path: root/ml/dlib/dlib/svm/structural_sequence_segmentation_trainer.h
diff options
context:
space:
mode:
Diffstat (limited to 'ml/dlib/dlib/svm/structural_sequence_segmentation_trainer.h')
-rw-r--r--ml/dlib/dlib/svm/structural_sequence_segmentation_trainer.h281
1 files changed, 0 insertions, 281 deletions
diff --git a/ml/dlib/dlib/svm/structural_sequence_segmentation_trainer.h b/ml/dlib/dlib/svm/structural_sequence_segmentation_trainer.h
deleted file mode 100644
index 2e0214008..000000000
--- a/ml/dlib/dlib/svm/structural_sequence_segmentation_trainer.h
+++ /dev/null
@@ -1,281 +0,0 @@
-// Copyright (C) 2013 Davis E. King (davis@dlib.net)
-// License: Boost Software License See LICENSE.txt for the full license.
-#ifndef DLIB_STRUCTURAL_SEQUENCE_sEGMENTATION_TRAINER_Hh_
-#define DLIB_STRUCTURAL_SEQUENCE_sEGMENTATION_TRAINER_Hh_
-
-#include "structural_sequence_segmentation_trainer_abstract.h"
-#include "structural_sequence_labeling_trainer.h"
-#include "sequence_segmenter.h"
-
-namespace dlib
-{
-
-// ----------------------------------------------------------------------------------------
-
- template <
- typename feature_extractor
- >
- class structural_sequence_segmentation_trainer
- {
- public:
- typedef typename feature_extractor::sequence_type sample_sequence_type;
- typedef std::vector<std::pair<unsigned long, unsigned long> > segmented_sequence_type;
-
- typedef sequence_segmenter<feature_extractor> trained_function_type;
-
- explicit structural_sequence_segmentation_trainer (
- const feature_extractor& fe_
- ) : trainer(impl_ss::feature_extractor<feature_extractor>(fe_))
- {
- loss_per_missed_segment = 1;
- loss_per_false_alarm = 1;
- }
-
- structural_sequence_segmentation_trainer (
- )
- {
- loss_per_missed_segment = 1;
- loss_per_false_alarm = 1;
- }
-
- const feature_extractor& get_feature_extractor (
- ) const { return trainer.get_feature_extractor().fe; }
-
- void set_num_threads (
- unsigned long num
- )
- {
- trainer.set_num_threads(num);
- }
-
- unsigned long get_num_threads (
- ) const
- {
- return trainer.get_num_threads();
- }
-
- void set_epsilon (
- double eps_
- )
- {
- // make sure requires clause is not broken
- DLIB_ASSERT(eps_ > 0,
- "\t void structural_sequence_segmentation_trainer::set_epsilon()"
- << "\n\t eps_ must be greater than 0"
- << "\n\t eps_: " << eps_
- << "\n\t this: " << this
- );
-
- trainer.set_epsilon(eps_);
- }
-
- double get_epsilon (
- ) const { return trainer.get_epsilon(); }
-
- unsigned long get_max_iterations (
- ) const { return trainer.get_max_iterations(); }
-
- void set_max_iterations (
- unsigned long max_iter
- )
- {
- trainer.set_max_iterations(max_iter);
- }
-
- void set_max_cache_size (
- unsigned long max_size
- )
- {
- trainer.set_max_cache_size(max_size);
- }
-
- unsigned long get_max_cache_size (
- ) const
- {
- return trainer.get_max_cache_size();
- }
-
- void be_verbose (
- )
- {
- trainer.be_verbose();
- }
-
- void be_quiet (
- )
- {
- trainer.be_quiet();
- }
-
- void set_oca (
- const oca& item
- )
- {
- trainer.set_oca(item);
- }
-
- const oca get_oca (
- ) const
- {
- return trainer.get_oca();
- }
-
- void set_c (
- double C_
- )
- {
- // make sure requires clause is not broken
- DLIB_ASSERT(C_ > 0,
- "\t void structural_sequence_segmentation_trainer::set_c()"
- << "\n\t C_ must be greater than 0"
- << "\n\t C_: " << C_
- << "\n\t this: " << this
- );
-
- trainer.set_c(C_);
- }
-
- double get_c (
- ) const
- {
- return trainer.get_c();
- }
-
- void set_loss_per_missed_segment (
- double loss
- )
- {
- // make sure requires clause is not broken
- DLIB_ASSERT(loss >= 0,
- "\t void structural_sequence_segmentation_trainer::set_loss_per_missed_segment(loss)"
- << "\n\t invalid inputs were given to this function"
- << "\n\t loss: " << loss
- << "\n\t this: " << this
- );
-
- loss_per_missed_segment = loss;
-
- if (feature_extractor::use_BIO_model)
- {
- trainer.set_loss(impl_ss::BEGIN, loss_per_missed_segment);
- trainer.set_loss(impl_ss::INSIDE, loss_per_missed_segment);
- }
- else
- {
- trainer.set_loss(impl_ss::BEGIN, loss_per_missed_segment);
- trainer.set_loss(impl_ss::INSIDE, loss_per_missed_segment);
- trainer.set_loss(impl_ss::LAST, loss_per_missed_segment);
- trainer.set_loss(impl_ss::UNIT, loss_per_missed_segment);
- }
- }
-
- double get_loss_per_missed_segment (
- ) const
- {
- return loss_per_missed_segment;
- }
-
- void set_loss_per_false_alarm (
- double loss
- )
- {
- // make sure requires clause is not broken
- DLIB_ASSERT(loss >= 0,
- "\t void structural_sequence_segmentation_trainer::set_loss_per_false_alarm(loss)"
- << "\n\t invalid inputs were given to this function"
- << "\n\t loss: " << loss
- << "\n\t this: " << this
- );
-
- loss_per_false_alarm = loss;
-
- trainer.set_loss(impl_ss::OUTSIDE, loss_per_false_alarm);
- }
-
- double get_loss_per_false_alarm (
- ) const
- {
- return loss_per_false_alarm;
- }
-
- const sequence_segmenter<feature_extractor> train(
- const std::vector<sample_sequence_type>& x,
- const std::vector<segmented_sequence_type>& y
- ) const
- {
-
- // make sure requires clause is not broken
- DLIB_ASSERT(is_sequence_segmentation_problem(x,y) == true,
- "\t sequence_segmenter structural_sequence_segmentation_trainer::train(x,y)"
- << "\n\t invalid inputs were given to this function"
- << "\n\t x.size(): " << x.size()
- << "\n\t is_sequence_segmentation_problem(x,y): " << is_sequence_segmentation_problem(x,y)
- << "\n\t this: " << this
- );
-
- std::vector<std::vector<unsigned long> > labels(y.size());
- if (feature_extractor::use_BIO_model)
- {
- // convert y into tagged BIO labels
- for (unsigned long i = 0; i < labels.size(); ++i)
- {
- labels[i].resize(x[i].size(), impl_ss::OUTSIDE);
- for (unsigned long j = 0; j < y[i].size(); ++j)
- {
- const unsigned long begin = y[i][j].first;
- const unsigned long end = y[i][j].second;
- if (begin != end)
- {
- labels[i][begin] = impl_ss::BEGIN;
- for (unsigned long k = begin+1; k < end; ++k)
- labels[i][k] = impl_ss::INSIDE;
- }
- }
- }
- }
- else
- {
- // convert y into tagged BILOU labels
- for (unsigned long i = 0; i < labels.size(); ++i)
- {
- labels[i].resize(x[i].size(), impl_ss::OUTSIDE);
- for (unsigned long j = 0; j < y[i].size(); ++j)
- {
- const unsigned long begin = y[i][j].first;
- const unsigned long end = y[i][j].second;
- if (begin != end)
- {
- if (begin+1==end)
- {
- labels[i][begin] = impl_ss::UNIT;
- }
- else
- {
- labels[i][begin] = impl_ss::BEGIN;
- for (unsigned long k = begin+1; k+1 < end; ++k)
- labels[i][k] = impl_ss::INSIDE;
- labels[i][end-1] = impl_ss::LAST;
- }
- }
- }
- }
- }
-
- sequence_labeler<impl_ss::feature_extractor<feature_extractor> > temp;
- temp = trainer.train(x, labels);
- return sequence_segmenter<feature_extractor>(temp.get_weights(), trainer.get_feature_extractor().fe);
- }
-
- private:
-
- structural_sequence_labeling_trainer<impl_ss::feature_extractor<feature_extractor> > trainer;
- double loss_per_missed_segment;
- double loss_per_false_alarm;
- };
-
-// ----------------------------------------------------------------------------------------
-
-}
-
-#endif // DLIB_STRUCTURAL_SEQUENCE_sEGMENTATION_TRAINER_Hh_
-
generated by cgit v1.2.3 (git 2.39.1) at 2024-05-19 07:30:32 +0000