Implements Bhattacharyya distance based on normal (gaussian) model to serve as feature selection criterion. More...

#include <criterion_normal_bhattacharyya.hpp>

Inheritance diagram for FST::Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >:

Public Types
typedef Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >	parent
	base class: the normal-model template-method skeleton
typedef Clonable_Impl< Criterion_Normal_Bhattacharyya, parent >	parent_impl
	implements clone(); sharing/stateless_clone throw in Criterion
typedef std::shared_ptr< DATAACCESSOR >	PDataAccessor
	shared pointer to the data accessor the model is learned from
typedef std::shared_ptr< SUBSET >	PSubset
	shared pointer to the feature subset being evaluated
Public Types inherited from FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >
typedef std::shared_ptr< DATAACCESSOR >	PDataAccessor
	shared pointer to the data accessor the model is learned from
typedef std::shared_ptr< SUBSET >	PSubset
	shared pointer to the feature subset being evaluated
Public Types inherited from FST::Criterion_Filter< RETURNTYPE, SUBSET >
typedef std::shared_ptr< SUBSET >	PSubset
	shared pointer to the feature subset being evaluated
Public Types inherited from FST::Criterion< RETURNTYPE, SUBSET >
typedef std::shared_ptr< SUBSET >	PSubset
	shared pointer to the feature subset being evaluated

Protected Member Functions
virtual const char *	criterion_name () const override
	class name, used in output and error messages
virtual void	allocate_buffers () override
	(re)allocate criterion-specific work buffers for get_n() features (use the alloc_* helpers)
virtual void	update_derived_model () override
virtual bool	evaluate_narrowed (RETURNTYPE &result, const PSubset sub) override
	narrow remaining buffers to sub, redim work buffers to get_d(), compute the criterion value. On entry _model and _meandif have ALREADY been narrowed to `sub` by evaluate(), so the implementation sees only the d selected features; get_d() is that d, and _meandif->at(i) addresses the narrowed positions. `sub` is non-empty (evaluate() rejects d==0 before the call).
Protected Member Functions inherited from FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >
	Criterion_Normal (const Criterion_Normal &cn)
	Copy-constructor; deep-copies _model and _meandif (subclasses copy their own buffers separately).
void	alloc_vector (std::unique_ptr< Indexed_Vector< DATATYPE, DIMTYPE, SUBSET > > &v)
	lazy (re)allocation of a work vector for get_n() features, for use from allocate_buffers()
template<typename MATRIXVALUETYPE>
void	alloc_matrix (std::unique_ptr< Indexed_Matrix< MATRIXVALUETYPE, DIMTYPE, SUBSET > > &m, const bool LUstorage=false)
	lazy (re)allocation of a work matrix for get_n() features; LUstorage as required by Indexed_Matrix::LUdecompose() temp storage
Protected Member Functions inherited from FST::Clonable
void	set_cloned (const bool cloned=true)
	marks/unmarks this instance as a clone; call from clone()/stateless_clone() overrides (Clonable_Impl does this automatically)
void	set_sharing (const bool sharing=true)
	marks/unmarks this instance as sharing (see is_sharing())
void	set_sharing_cloned (const bool cloned=true, const bool sharing=true)
	sets both flags at once; call from sharing_clone() overrides (Clonable_Impl does this automatically)

Private Member Functions
	Criterion_Normal_Bhattacharyya (const Criterion_Normal_Bhattacharyya &cnb)
	Copy-constructor; deep-copies the four criterion-specific work buffers (base _model/_meandif copied by parent_impl).

Private Attributes
friend	parent_impl
std::unique_ptr< Indexed_Matrix< DATATYPE, DIMTYPE, SUBSET > >	_cov12
	(cov[0]+cov[1]), computed by update_derived_model()
std::unique_ptr< Indexed_Matrix< DATATYPE, DIMTYPE, SUBSET > >	_cov12_div2
	_cov12/2, the pooled covariance whose determinant enters the Bhattacharyya distance
std::unique_ptr< Indexed_Matrix< REALTYPE, DIMTYPE, SUBSET > >	_invbuf
	inverse of the narrowed _cov12, used in the quadratic-form term
std::unique_ptr< Indexed_Matrix< REALTYPE, DIMTYPE, SUBSET > >	_LUtemp
	scratch LU-decomposition storage, reused for each matrix inversion/determinant

Additional Inherited Members
Public Member Functions inherited from FST::Clonable_Impl< Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >, Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR > >
Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR > *	clone () const override
	dispatches to the DEEP_KIND mechanism (default CLONE_DEEP: Derived's copy-constructor)
Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR > *	sharing_clone () const override
	dispatches to the SHARING_KIND mechanism (default CLONE_INHERIT: defers to Base, which throws by family convention)
Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR > *	stateless_clone () const override
	dispatches to the STATELESS_KIND mechanism (default CLONE_INHERIT: defers to Base, which throws by family convention)
Public Member Functions inherited from FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >
virtual bool	initialize (PDataAccessor da)
	template method: learn model, compute _meandif, then allocate_buffers() + update_derived_model().
virtual bool	evaluate (RETURNTYPE &result, const PSubset sub) override
	template method: narrow model and _meandif to sub, then evaluate_narrowed()
virtual bool	is_monotonic () const override
DIMTYPE	get_n () const
	the full (raw, unnarrowed) feature count the model was learned for
DIMTYPE	get_d () const
	the currently active (narrowed) feature count, see evaluate()
virtual std::ostream &	print (std::ostream &os) const override
	writes a human-readable identification of the object; base default writes nothing
Public Member Functions inherited from FST::Criterion< RETURNTYPE, SUBSET >
Criterion *	sharing_clone () const override
Criterion *	stateless_clone () const override
Public Member Functions inherited from FST::Clonable
bool	is_clone () const
bool	is_sharing () const
	true if this instance is a sharing_clone() result (referencing, not owning, the source's structures)
bool	is_sharing_clone () const
	true if this instance is BOTH a clone and sharing – i.e. specifically a sharing_clone() result, not a clone()/stateless_clone() one
Protected Attributes inherited from FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >
std::unique_ptr< Model_Normal< DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR > >	_model
	the learned per-class normal (mean/covariance) model, narrowed in evaluate()
std::unique_ptr< Indexed_Vector< DATATYPE, DIMTYPE, SUBSET > >	_meandif
	mean[0]-mean[1], shared by all two-class normal criteria

Detailed Description

template<class RETURNTYPE, typename DATATYPE, typename REALTYPE, typename IDXTYPE, typename DIMTYPE, class SUBSET, class DATAACCESSOR>
class FST::Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >

Implements Bhattacharyya distance based on normal (gaussian) model to serve as feature selection criterion.

For the two classes modelled as Gaussians (mu0,S0) and (mu1,S1) restricted to the d selected features, with m = mu0-mu1 and S = (S0+S1)/2, the value returned is

B = 1/8 * m^T S^-1 m  +  1/2 * ln( det(S) / sqrt(det(S0)*det(S1)) )

i.e. the standard Bhattacharyya distance between two normal distributions: a mean-separation term plus a covariance-dissimilarity term. Higher is better, the value is non-negative and grows with subset size (monotonic w.r.t. cardinality, hence usable with Branch & Bound). evaluate_narrowed() computes the first term equivalently as 0.25 * m^T (S0+S1)^-1 m, which saves halving the summed covariance for the inversion.

Note: Defined for two-class problems only; Requires non-singular per-class covariances on the evaluated subset - see the remark in evaluate_narrowed()

Examples: demo55.cpp.

Member Function Documentation

◆ allocate_buffers()

template<class RETURNTYPE, typename DATATYPE, typename REALTYPE, typename IDXTYPE, typename DIMTYPE, class SUBSET, class DATAACCESSOR>

virtual void FST::Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >::allocate_buffers ( )

inlineoverrideprotectedvirtual

(re)allocate criterion-specific work buffers for get_n() features (use the alloc_* helpers)

Implements FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >.

◆ criterion_name()

template<class RETURNTYPE, typename DATATYPE, typename REALTYPE, typename IDXTYPE, typename DIMTYPE, class SUBSET, class DATAACCESSOR>

virtual const char * FST::Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >::criterion_name ( ) const

inlineoverrideprotectedvirtual

class name, used in output and error messages

Implements FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >.

◆ evaluate_narrowed()

template<class RETURNTYPE, typename DATATYPE, typename REALTYPE, typename IDXTYPE, typename DIMTYPE, class SUBSET, class DATAACCESSOR>

bool FST::Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >::evaluate_narrowed	(	RETURNTYPE &	result,
		const PSubset	sub )

overrideprotectedvirtual

narrow remaining buffers to sub, redim work buffers to get_d(), compute the criterion value. On entry _model and _meandif have ALREADY been narrowed to sub by evaluate(), so the implementation sees only the d selected features; get_d() is that d, and _meandif->at(i) addresses the narrowed positions. sub is non-empty (evaluate() rejects d==0 before the call).

Implements FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >.

◆ update_derived_model()

template<class RETURNTYPE, typename DATATYPE, typename REALTYPE, typename IDXTYPE, typename DIMTYPE, class SUBSET, class DATAACCESSOR>

virtual void FST::Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >::update_derived_model ( )

inlineoverrideprotectedvirtual

precompute criterion-specific derivations of the freshly learned model (_meandif is already computed)

Implements FST::Criterion_Normal< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >.

Member Data Documentation

◆ parent_impl

template<class RETURNTYPE, typename DATATYPE, typename REALTYPE, typename IDXTYPE, typename DIMTYPE, class SUBSET, class DATAACCESSOR>

friend FST::Criterion_Normal_Bhattacharyya< RETURNTYPE, DATATYPE, REALTYPE, IDXTYPE, DIMTYPE, SUBSET, DATAACCESSOR >::parent_impl

private

grants Clonable_Impl access to the copy-constructor

The documentation for this class was generated from the following file:

/Users/psms/dev/devtest1/_src_criteria/criterion_normal_bhattacharyya.hpp

Public Types

Protected Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ allocate_buffers()

◆ criterion_name()

◆ evaluate_narrowed()

◆ update_derived_model()

Member Data Documentation

◆ parent_impl