WeightedPatternResponse.h File Reference

WeightedPatternResponse methods and utility functions. More...

#include <cmath>
#include "Classifier/DecisionStump.h"
#include "Classifier/MultiClassDecisionStump.h"
#include "Classifier/RealDecisionStump.h"

Go to the source code of this file.

Classes
struct	BinaryWeightedPatternResponse< ResponseType >
struct	WeightedPatternResponse< ResponseType >
class	AdaBoostMetric
	AdaBoost W+ metric (or any metric based on weighted pattern sum) for DecisionStumpPolicy (in this case only used as container for the param recovered) using PatternResponse. More...
class	GentleAdaBoostMetric
class	RealAdaBoostMetric

Typedefs
typedef BinaryWeightedPatternResponse < int >	PatternResponse
	A weighted pattern response with integer values.

Functions
template<class Set >
void	__InitializePatternResponse (BinaryWeightedPatternResponse< int > *store, int n_feature, const Set &set)
	set up d field in BinaryWeightedPatternResponse
template<class FeatureExtractor , class Set >
void	ComputeFeaturesResponse (BinaryWeightedPatternResponse< int > *store, const FeatureExtractor *h, int n_feature, const Set &set, int i0, int i1)
template<class FeatureExtractor , class Set >
void	ExtractFeature (BinaryWeightedPatternResponse< int > *store, const FeatureExtractor &h, const Set &set)
	extract from templates feature using h and put in store, and associating the weighted category d
void	GenerateBucket (BinaryWeightedPatternResponse< int > *store, int n_bucket, const BinaryWeightedPatternResponse< int > *source, int n_element)
template<class FeatureExtractor , class Set >
void	ExtractFeatureAndBucket (BinaryWeightedPatternResponse< int > *store, const FeatureExtractor &h, const Set &set, int n_bucket, int *value)
template<class FeatureExtractor , class Set >
void	ExtractFeatureSubPart (WeightedPatternResponse< int > *store, const FeatureExtractor *h, int n_feature, const Set &set, int i0, int i1)
template<class FeatureExtractor , class Set >
void	ExtractFeature (WeightedPatternResponse< int > *store, const FeatureExtractor &h, const Set &set)
	extract from templates feature using h and put in store, and associating the weighted category d
void	sort_pattern (PatternResponse *store, int n)

Detailed Description

WeightedPatternResponse methods and utility functions.

Function Documentation

template<class FeatureExtractor , class Set >

void ComputeFeaturesResponse	(	BinaryWeightedPatternResponse< int > *	store,
		const FeatureExtractor *	h,
		int	n_feature,
		const Set &	set,
		int	i0,
		int	i1
	)

Used when multiple feature are evaluated at the same time on the same set, in a multi-thread flavor

Parameters

i0,i1

range of training set evaluated

template<class FeatureExtractor , class Set >

void ExtractFeatureAndBucket	(	BinaryWeightedPatternResponse< int > *	store,
		const FeatureExtractor &	h,
		const Set &	set,
		int	n_bucket,
		int *	value
	)

extract from templates feature using h and put in store, and associating the weighted category d

Parameters

value

a working vector set.Size() large

template<class FeatureExtractor , class Set >

void ExtractFeatureSubPart	(	WeightedPatternResponse< int > *	store,
		const FeatureExtractor *	h,
		int	n_feature,
		const Set &	set,
		int	i0,
		int	i1
	)

Used when multiple feature are evaluated at the same time on the same set, in a multi-thread flavor

Parameters

i0,i1

range of training set evaluated

void GenerateBucket	(	BinaryWeightedPatternResponse< int > *	store,
		int	n_bucket,
		const BinaryWeightedPatternResponse< int > *	source,
		int	n_element
	)

Generate only bucket from a precompute response value array

Parameters

store	an output histogram
n_bucket	size of the histogram, number of bin/bucket
source	precomputed response with weight
n_element	size of precomputed response

void sort_pattern	(	PatternResponse *	store,
		int	n
	)

sort pattern with ascending "value". use before find_threshold