FeatureNormalizer Class Reference

Feature Normalizer. More...

#include <FeatureProcess.h>

Inheritance diagram for FeatureNormalizer:

Public Member Functions
	FeatureNormalizer (const string &feature_name)
	FeatureNormalizer (const string &feature_name, string init_string)
string	select_learn_matrix (const vector< string > &matrix_tags) const
	Will be called before learn to create new version for the matrix if needed - in parallel of existing matrix.
int	Learn (MedFeatures &features, unordered_set< int > &ids)
int	_apply (MedFeatures &features, unordered_set< int > &ids)
void	reverse_apply (float &feature_value) const
	Reverse action of Apply - denorm feature value.
int	init (map< string, string > &mapper)
	The parsed fields from init command.
void	init_defaults ()
virtual void	copy (FeatureProcessor *processor)
Public Member Functions inherited from FeatureProcessor
virtual void	clear ()
void	init_defaults ()
virtual void	set_feature_name (const string &feature_name)
virtual string	get_feature_name ()
virtual void	get_feature_names (vector< string > &feature_names)
int	learn (MedFeatures &features)
	PostProcess of MedFeatures - on all ids.
int	learn (MedFeatures &features, unordered_set< int > &ids)
virtual int	_apply (MedFeatures &features, unordered_set< int > &ids, bool learning)
virtual int	_conditional_apply (MedFeatures &features, unordered_set< int > &ids, unordered_set< string > &req_features, bool learning)
int	apply (MedFeatures &features, bool learning)
	PostProcess of MedFeatures - on all or a subset of the ids calls virtaul function "_apply/_conditional_apply" for the specific implementation.
int	apply (MedFeatures &features, unordered_set< string > &req_features, bool learning)
int	apply (MedFeatures &features, unordered_set< int > &ids, bool learning)
int	apply (MedFeatures &features, unordered_set< int > &ids, unordered_set< string > &req_features, bool learning)
int	apply (MedFeatures &features)
int	apply (MedFeatures &features, unordered_set< string > &req_features)
int	apply (MedFeatures &features, unordered_set< int > &ids)
int	apply (MedFeatures &features, unordered_set< int > &ids, unordered_set< string > &req_features)
virtual int	init (void *processor_params)
virtual int	filter (unordered_set< string > &features)
	Filter according to a subset of features.
string	resolve_feature_name (MedFeatures &features, string substr)
	Utility : get corresponding name in MedFeatures.
virtual bool	are_features_affected (unordered_set< string > &out_req_features)
	check if a set of features is affected by the current processor
virtual void	update_req_features_vec (unordered_set< string > &out_req_features, unordered_set< string > &in_req_features)
	update sets of required as input according to set required as output to processor Empty sets = require everything.
virtual bool	is_selector ()
	allows testing if this feature processor is a selector
void *	new_polymorphic (string derived_class_name)
	for polymorphic classes that want to be able to serialize/deserialize a pointer * to the derived class given its type one needs to implement this function to return a new to the derived class given its type (as in my_type)
size_t	get_processor_size ()
size_t	processor_serialize (unsigned char *blob)
virtual void	dprint (const string &pref, int rp_flag)
Public Member Functions inherited from SerializableObject
virtual int	version () const
	Relevant for serializations.
virtual string	my_class_name () const
	For better handling of serializations it is highly recommended that each SerializableObject inheriting class will implement the next method.
virtual void	serialized_fields_name (vector< string > &field_names) const
	The names of the serialized fields.
virtual void	pre_serialization ()
virtual void	post_deserialization ()
virtual size_t	get_size ()
	Gets bytes sizes for serializations.
virtual size_t	serialize (unsigned char *blob)
	Serialiazing object to blob memory. return number ob bytes wrote to memory.
virtual size_t	deserialize (unsigned char *blob)
	Deserialiazing blob to object. returns number of bytes read.
size_t	serialize_vec (vector< unsigned char > &blob)
size_t	deserialize_vec (vector< unsigned char > &blob)
virtual size_t	serialize (vector< unsigned char > &blob)
virtual size_t	deserialize (vector< unsigned char > &blob)
virtual int	read_from_file (const string &fname)
	read and deserialize model
virtual int	write_to_file (const string &fname)
	serialize model and write to file
virtual int	read_from_file_unsafe (const string &fname)
	read and deserialize model without checking version number - unsafe read
int	init_from_string (string init_string)
	Init from string.
int	init_params_from_file (string init_file)
int	init_param_from_file (string file_str, string &param)
int	update_from_string (const string &init_string)
virtual int	update (map< string, string > &map)
	Virtual to update object from parsed fields.
virtual string	object_json () const

Data Fields
float	missing_value
	Missing Value.
bool	normalizeSd
	Normalize Standard Deviation.
bool	fillMissing
	Fill missing values with mean.
float	mean
	Moments.
float	sd
int	resolution = 0
	resolution : if > 0 , will keep only the given number of digits after the point.
float	resolution_bin
	A factor to divide by - take floor and then multiply by again. Used in resolution_only mode.
int	max_samples = 0
	Utility : maximum number of samples to take for moments calculations.
bool	resolution_only = false
	if resolution only
int	verbosity = 0
	verbosity
bool	use_linear_transform = false
	If true will convert into linear transform from lower prctile to high prctile and has triming value.
float	max_val_prctile = 1
float	max_val_for_triming = 2
float	prctile_th = (float)0.001
float	min_x
float	max_x
	parmeters of the transformation
Data Fields inherited from FeatureProcessor
string	feature_name = "unset_feature_name"
	Feature name ( + name as appears in MedFeatures) ;.
string	resolved_feature_name
FeatureProcessorTypes	processor_type = FTR_PROCESS_LAST
int	learn_nthreads
int	clean_nthreads

Additional Inherited Members
Static Public Member Functions inherited from FeatureProcessor
static FeatureProcessor *	make_processor (string processor_name)
static FeatureProcessor *	make_processor (FeatureProcessorTypes type)
static FeatureProcessor *	make_processor (string processor_name, string params)
static FeatureProcessor *	make_processor (FeatureProcessorTypes type, string params)

Detailed Description

Feature Normalizer.

To Use this selector specify "normalizer" in the fp_type

Member Function Documentation

_apply()

int FeatureNormalizer::_apply ( MedFeatures &  features, unordered_set< int > &  ids  )

virtual

Reimplemented from FeatureProcessor.

copy()

virtual void FeatureNormalizer::copy ( FeatureProcessor *  processor )

inlinevirtual

Reimplemented from FeatureProcessor.

init()

int FeatureNormalizer::init ( map< string, string > &  mapper )

virtual

The parsed fields from init command.

        if (field == "missing_value") missing_value = stof(entry.second);
        else if (field == "normalizeSd") normalizeSd = (med_stoi(entry.second) != 0);
        else if (field == "resolution_only") resolution_only = (med_stoi(entry.second) != 0);
        else if (field == "fillMissing") fillMissing = (med_stoi(entry.second) != 0);
        else if (field == "max_samples") max_samples = med_stoi(entry.second);
        else if (field == "resolution") resolution = med_stoi(entry.second);
        else if (field == "resolution_bin") resolution_bin = med_stof(entry.second);
        else if (field == "signal") set_feature_name(entry.second);
        else if (field == "vorbosity") verbosity = med_stoi(entry.second);
        else if (field == "use_linear_transform") use_linear_transform = med_stoi(entry.second) > 0;
        else if (field == "max_val_prctile") max_val_prctile = med_stof(entry.second);
        else if (field == "prctile_th") prctile_th = med_stof(entry.second);
        else if (field == "max_val_for_triming") max_val_for_triming = med_stof(entry.second);
        else if (field != "names" && field != "fp_type" && field != "tag")
            MLOG("Unknonw parameter \'%s\' for FeatureNormalizer\n", field.c_str());

[FeatureNormalizer::init]

[FeatureNormalizer::init]

Reimplemented from FeatureProcessor.

Learn()

int FeatureNormalizer::Learn ( MedFeatures &  features, unordered_set< int > &  ids  )

virtual

Reimplemented from FeatureProcessor.

select_learn_matrix()

string FeatureNormalizer::select_learn_matrix ( const vector< string > &  matrix_tags ) const

virtual

Will be called before learn to create new version for the matrix if needed - in parallel of existing matrix.

Reimplemented from FeatureProcessor.

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

• Internal/MedProcessTools/MedProcessTools/FeatureProcess.h
• Internal/MedProcessTools/MedProcessTools/FeatureProcess.cpp