CPruneVarSubMean Class Reference


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 28 of file PruneVarSubMean.h.

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)
virtual const char * get_name ()

Protected Attributes

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

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();

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

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.

virtual const char* CPruneVarSubMean::get_name (  )  [virtual]
Returns:
object name

Definition at line 59 of file PruneVarSubMean.h.

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 71 of file PruneVarSubMean.h.

int32_t* CPruneVarSubMean::idx [protected]

idx

Definition at line 63 of file PruneVarSubMean.h.

true when already initialized

Definition at line 74 of file PruneVarSubMean.h.

mean

Definition at line 65 of file PruneVarSubMean.h.

int32_t CPruneVarSubMean::num_idx [protected]

num idx

Definition at line 69 of file PruneVarSubMean.h.

std

Definition at line 67 of file PruneVarSubMean.h.


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

SHOGUN Machine Learning Toolbox - Documentation