BinnedLinearModels : Apply a set of liner models to generate features. More...

#include <FeatureGenerator.h>

Inheritance diagram for BinnedLmEstimates:

Public Member Functions
void	set_names ()
	Naming.

	BinnedLmEstimates (string _signalName)

	BinnedLmEstimates (string _signalName, string init_string)

void	set (string &_signalName)

void	set (string &_signalName, BinnedLmEstimatesParams *_params)

void	init_defaults ()

int	init (map< string, string > &mapper)
	The parsed fields from init command.

virtual void	copy (FeatureGenerator *generator)

int	_learn (MedPidRepository &rep, const MedSamples &samples, vector< RepProcessor * > processors)
	Learn a generator.

int	_generate (PidDynamicRec &rec, MedFeatures &features, int index, int num, vector< float * > &_p_data)
	generate new feature(s)

int	filter_features (unordered_set< string > &validFeatures)
	Filter generated features according to a set. return number of valid features (does not affect single-feature genertors, just returns 1/0 if feature name in set)

void	get_p_data (MedFeatures &features, vector< float * > &_p_data)

void	set_signal_ids (MedSignals &sigs)

void	set_sampling_strategy (string &strategy)

void	prepare_for_age (PidDynamicRec &rec, UniversalSigVec &ageUsv, int &age, int &byear)

void	prepare_for_age (MedPidRepository &rep, int id, UniversalSigVec &ageUsv, int &age, int &byear)

void	get_age (int time, int time_unit_from, int &age, int byear)

void	dprint (const string &pref, int fg_flag)

void	print ()

Public Member Functions inherited from FeatureGenerator
virtual void	prepare (MedFeatures &features, MedPidRepository &rep, MedSamples &samples)

void	get_p_data (MedFeatures &features)

virtual void	clear ()

void	get_required_signal_names (unordered_set< string > &signalNames)

virtual void	set_required_signal_ids (MedDictionarySections &dict)

void	get_required_signal_ids (unordered_set< int > &signalIds)

virtual void	get_generated_features (unordered_set< string > &names_list)

virtual void	init_tables (MedDictionarySections &dict)

virtual void	fit_for_repository (MedPidRepository &rep)
	Prepartion and adjustment for model based on repository.

int	learn (MedPidRepository &rep, const MedSamples &samples, vector< RepProcessor * > processors)

int	learn (MedPidRepository &rep, const MedSamples &samples)

int	_generate (PidDynamicRec &in_rep, MedFeatures &features, int index, int num)

int	generate (PidDynamicRec &in_rep, MedFeatures &features, int index, int num)

int	generate (PidDynamicRec &in_rep, MedFeatures &features)

int	generate (MedPidRepository &rep, int id, MedFeatures &features)

int	generate (MedPidRepository &rep, int id, MedFeatures &features, int index, int num)

virtual int	_generate (MedFeatures &features)

int	generate (MedFeatures &features)

virtual int	init (void *generator_params)

virtual int	nfeatures ()

virtual void	get_required_signal_categories (unordered_map< string, vector< string > > &signal_categories_in_use) const
	returns for each used signal it's used categories

virtual void	make_summary ()

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_generator_size ()

size_t	generator_serialize (unsigned char *blob)

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
string	signalName

int	signalId

int	bdateId

int	genderId

BinnedLmEstimatesParams	params

BinnedLMSamplingStrategy	sampling_strategy = BINNED_LM_TAKE_ALL

vector< MedLM >	models

vector< float >	xmeans

vector< float >	xsdvs

vector< float >	ymeans

vector< float >	ysdvs

vector< vector< float > >	means = { {}, {} }

int	time_unit_periods = MedTime::Undefined
	the time unit in which the periods are given. Default: Undefined

int	time_unit_sig = MedTime::Undefined
	the time init in which the signal is given. Default: Undefined

int	time_channel = 0
	n >= 0 : use time channel n , default: 0.

int	val_channel = 0
	n >= 0 : use val channel n , default : 0.

Data Fields inherited from FeatureGenerator
FeatureGeneratorTypes	generator_type = FTR_GEN_LAST
	Type.

vector< string >	names
	Feature name.

int	learn_nthreads = 16

int	pred_nthreads = 16

float	missing_val = (float)MED_MAT_MISSING_VALUE
	Missing value.

vector< string >	tags
	Tags - for defining labels or groups. may be used later for filtering for example.

int	iGenerateWeights = 0
	Feature/Weights generator.

vector< float * >	p_data

vector< string >	req_signals

vector< int >	req_signal_ids

int	serial_id

Additional Inherited Members
Static Public Member Functions inherited from FeatureGenerator
static FeatureGenerator *	make_generator (string name)

static FeatureGenerator *	make_generator (string name, string params)

static FeatureGenerator *	make_generator (FeatureGeneratorTypes type)

static FeatureGenerator *	make_generator (FeatureGeneratorTypes type, string params)

static FeatureGenerator *	create_generator (string &params)

Detailed Description

BinnedLinearModels : Apply a set of liner models to generate features.

Member Function Documentation

◆ _generate()

int BinnedLmEstimates::_generate	(	PidDynamicRec &	rec,
		MedFeatures &	features,
		int	index,
		int	num,
		vector< float * > &	_p_data
	)

virtual

generate new feature(s)

Reimplemented from FeatureGenerator.

◆ _learn()

int BinnedLmEstimates::_learn	(	MedPidRepository &	rep,
		const MedSamples &	samples,
		vector< RepProcessor * >	processors
	)

virtual

Learn a generator.

Reimplemented from FeatureGenerator.

◆ copy()

virtual void BinnedLmEstimates::copy ( FeatureGenerator * generator )

inlinevirtual

Reimplemented from FeatureGenerator.

◆ dprint()

void BinnedLmEstimates::dprint	(	const string &	pref,
		int	fg_flag
	)

virtual

Reimplemented from FeatureGenerator.

◆ filter_features()

int BinnedLmEstimates::filter_features ( unordered_set< string > & validFeatures )

virtual

Filter generated features according to a set. return number of valid features (does not affect single-feature genertors, just returns 1/0 if feature name in set)

Reimplemented from FeatureGenerator.

◆ get_p_data()

void BinnedLmEstimates::get_p_data	(	MedFeatures &	features,
		vector< float * > &	_p_data
	)

virtual

Reimplemented from FeatureGenerator.

◆ init()

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

virtual

The parsed fields from init command.

        if (field == "bin_bounds") {
            if (init_dvec(entry.second, params.bin_bounds) == -1) {
                fprintf(stderr, "Cannot initialize bin_bounds for LM\n");
                return -1;
            }
        }
        else if (field == "max_period") params.max_period = stoi(entry.second);
        else if (field == "min_period") params.min_period = stoi(entry.second);
        else if (field == "rfactor") params.rfactor = stof(entry.second);
        else if (field == "signalName" || field == "signal") signalName = entry.second;
        else if (field == "estimation_points") {
            if (init_dvec(entry.second, params.estimation_points) == -1) {
                fprintf(stderr, "Cannot initialize estimation_points for LM\n");
                return -1;
            }
        }
        else if (field == "time_unit") time_unit_periods = med_time_converter.string_to_type(entry.second);
        else if (field == "time_channel") time_channel = stoi(entry.second);
        else if (field == "val_channel") val_channel = stoi(entry.second);
        else if (field == "tags") boost::split(tags, entry.second, boost::is_any_of(","));
        else if (field == "sampling") set_sampling_strategy(entry.second);
        else if (field == "weights_generator") iGenerateWeights = stoi(entry.second);
        else if (field != "fg_type")
            MLOG("Unknonw parameter \'%s\' for BinnedLmEstimates\n", field.c_str());

[BinnedLmEstimates::init]

Reimplemented from FeatureGenerator.

◆ init_defaults()

void BinnedLmEstimates::init_defaults ( )

virtual

Reimplemented from FeatureGenerator.

◆ print()

void BinnedLmEstimates::print ( )

virtual

Reimplemented from FeatureGenerator.

◆ set_names()

void BinnedLmEstimates::set_names ( )

virtual

Naming.

Reimplemented from FeatureGenerator.

◆ set_signal_ids()

void BinnedLmEstimates::set_signal_ids ( MedSignals & sigs )

virtual

Reimplemented from FeatureGenerator.

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

Internal/MedProcessTools/MedProcessTools/FeatureGenerator.h
Internal/MedProcessTools/MedProcessTools/BinnedLmEstimates.cpp

Public Member Functions

Data Fields

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ _generate()

◆ _learn()

◆ copy()

◆ dprint()

◆ filter_features()

◆ get_p_data()

◆ init()

◆ init_defaults()

◆ print()

◆ set_names()

◆ set_signal_ids()