CPruneVarSubMean Class Reference

Inheritance diagram for CPruneVarSubMean:

Inheritance graph
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List of all members.

Public Member Functions

 CPruneVarSubMean (bool divide=true)
virtual ~CPruneVarSubMean ()
virtual bool init (CFeatures *f)
 initialize preprocessor from features
virtual bool load_init_data (FILE *src)
 initialize preprocessor from file
virtual bool save_init_data (FILE *dst)
 save init-data (like transforamtion matrices etc) to file
virtual void cleanup ()
 cleanup
virtual float64_tapply_to_feature_matrix (CFeatures *f)
virtual float64_tapply_to_feature_vector (float64_t *f, int32_t &len)

Protected Attributes

int32_t * idx
float64_tmean
float64_tstd
int32_t num_idx
bool divide_by_std
bool initialized
 true when already initialized


Detailed Description

Preprocessor PruneVarSubMean will substract the mean and remove features that have zero variance. It will optionally normalize standard deviation of features to 1 (by dividing by standard deviation of the feature)

Definition at line 26 of file PruneVarSubMean.h.


Constructor & Destructor Documentation

CPruneVarSubMean::CPruneVarSubMean ( bool  divide = true  ) 

constructor

Parameters:
divide if division shall be made

Definition at line 19 of file PruneVarSubMean.cpp.

CPruneVarSubMean::~CPruneVarSubMean (  )  [virtual]

Definition at line 25 of file PruneVarSubMean.cpp.


Member Function Documentation

float64_t * CPruneVarSubMean::apply_to_feature_matrix ( CFeatures f  )  [virtual]

apply preproc on feature matrix result in feature matrix return pointer to feature_matrix, i.e. f->get_feature_matrix();

apply preproc on feature matrix result in feature matrix return pointer to feature_matrix, i.e. f->get_feature_matrix();

Implements CSimplePreProc< float64_t >.

Definition at line 140 of file PruneVarSubMean.cpp.

float64_t * CPruneVarSubMean::apply_to_feature_vector ( float64_t f,
int32_t &  len 
) [virtual]

apply preproc on single feature vector result in feature matrix

apply preproc on single feature vector result in feature matrix

Implements CSimplePreProc< float64_t >.

Definition at line 176 of file PruneVarSubMean.cpp.

void CPruneVarSubMean::cleanup (  )  [virtual]

cleanup

clean up allocated memory

Implements CPreProc.

Definition at line 127 of file PruneVarSubMean.cpp.

bool CPruneVarSubMean::init ( CFeatures f  )  [virtual]

initialize preprocessor from features

Implements CPreProc.

Definition at line 31 of file PruneVarSubMean.cpp.

bool CPruneVarSubMean::load_init_data ( FILE *  src  )  [virtual]

initialize preprocessor from file

Implements CPreProc.

Definition at line 207 of file PruneVarSubMean.cpp.

bool CPruneVarSubMean::save_init_data ( FILE *  dst  )  [virtual]

save init-data (like transforamtion matrices etc) to file

Implements CPreProc.

Definition at line 233 of file PruneVarSubMean.cpp.


Member Data Documentation

divide by std

Definition at line 66 of file PruneVarSubMean.h.

int32_t* CPruneVarSubMean::idx [protected]

idx

Definition at line 58 of file PruneVarSubMean.h.

true when already initialized

Definition at line 69 of file PruneVarSubMean.h.

mean

Definition at line 60 of file PruneVarSubMean.h.

int32_t CPruneVarSubMean::num_idx [protected]

num idx

Definition at line 64 of file PruneVarSubMean.h.

std

Definition at line 62 of file PruneVarSubMean.h.


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

SHOGUN Machine Learning Toolbox - Documentation