iterative set explainer with (gibbs, GAN or other samples generator) or proxy predictor algorithm to get as close as we can to final prediction score with lowest variance with the smallest set as possible of varaibles More...

#include <ExplainWrapper.h>

Inheritance diagram for IterativeSetExplainer:

Public Member Functions
void	_learn (const MedFeatures &train_mat)
	overload function for ModelExplainer - easier API

void	explain (const MedFeatures &matrix, vector< map< string, float > > &sample_explain_reasons) const
	Virtual - return explain results in sample_feature_contrib.

void	post_deserialization ()

void	load_GIBBS (MedPredictor *original_pred, const GibbsSampler< float > &gibbs, const GibbsSamplingParams &sampling_args)

void	load_GAN (MedPredictor *original_pred, const string &gan_path)

void	load_MISSING (MedPredictor *original_pred)

void	load_sampler (MedPredictor *original_pred, unique_ptr< SamplesGenerator< float > > &&generator)

void	dprint (const string &pref) const

Public Member Functions inherited from ModelExplainer
virtual int	init (map< string, string > &mapper)
	Global init for general args in all explainers. initialize directly all args in GlobalExplainerParams.

virtual int	update (map< string, string > &mapper)
	Virtual to update object from parsed fields.

virtual void	Learn (const MedFeatures &train_mat)
	Learns from predictor and train_matrix (PostProcessor API)

void	Apply (MedFeatures &matrix)
	alias for explain

void	get_input_fields (vector< Effected_Field > &fields) const
	List of fields that are used by this post_processor.

void	get_output_fields (vector< Effected_Field > &fields) const
	List of fields that are being effected by this post_processor.

void	init_post_processor (MedModel &model)
	Init ModelExplainer from MedModel - copies predictor pointer, might save normalizers pointers.

virtual void	explain (MedFeatures &matrix) const
	Stores explain results in matrix.

void	dprint (const string &pref) const

Public Member Functions inherited from PostProcessor
void *	new_polymorphic (string dname)
	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)

virtual float	get_use_p ()

virtual int	get_use_split ()

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 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 string	object_json () const

Data Fields
GeneratorType	gen_type = GeneratorType::GIBBS
	generator type

string	generator_args = ""
	for learn

string	sampling_args = ""
	args for sampling

int	n_masks = 100
	how many test to conduct from shapley

bool	use_random_sampling = true
	If True will use random sampling - otherwise will sample mask size and than create it.

float	missing_value = MED_MAT_MISSING_VALUE
	missing value

float	sort_params_a
	weight for minimal distance from original score importance

float	sort_params_b
	weight for variance in prediction using imputation. the rest is change from prev

float	sort_params_k1
	weight for minimal distance from original score importance

float	sort_params_k2
	weight for variance in prediction using imputation. the rest is change from prev

int	max_set_size
	the size to look for to explain

Data Fields inherited from ModelExplainer
MedPredictor *	original_predictor = NULL
	predictor we're trying to explain

ExplainFilters	filters
	general filters of results

ExplainProcessings	processing
	processing of results, like groupings, COV

GlobalExplainerParams	global_explain_params

Data Fields inherited from PostProcessor
PostProcessorTypes	processor_type = PostProcessorTypes::FTR_POSTPROCESS_LAST

int	use_split = -1

float	use_p = 0.0

Additional Inherited Members
Static Public Member Functions inherited from ModelExplainer
static void	print_explain (MedSample &smp, int sort_mode=0)

Static Public Member Functions inherited from PostProcessor
static PostProcessor *	make_processor (const string &processor_name, const string &params="")

static PostProcessor *	make_processor (PostProcessorTypes type, const string &params="")

static PostProcessor *	create_processor (string &params)

Detailed Description

iterative set explainer with (gibbs, GAN or other samples generator) or proxy predictor algorithm to get as close as we can to final prediction score with lowest variance with the smallest set as possible of varaibles

Member Function Documentation

◆ _learn()

void IterativeSetExplainer::_learn ( const MedFeatures & train_mat )

virtual

overload function for ModelExplainer - easier API

Implements ModelExplainer.

◆ dprint()

void IterativeSetExplainer::dprint ( const string & pref ) const

virtual

Reimplemented from PostProcessor.

◆ explain()

void IterativeSetExplainer::explain	(	const MedFeatures &	matrix,
		vector< map< string, float > > &	sample_explain_reasons
	)		const

virtual

Virtual - return explain results in sample_feature_contrib.

Implements ModelExplainer.

◆ post_deserialization()

void IterativeSetExplainer::post_deserialization ( )

virtual

Reimplemented from SerializableObject.

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

Internal/MedProcessTools/MedProcessTools/ExplainWrapper.h
Internal/MedProcessTools/MedProcessTools/ExplainWrapper.cpp

Public Member Functions

Data Fields

Additional Inherited Members

Detailed Description

Member Function Documentation

◆ _learn()

◆ dprint()

◆ explain()

◆ post_deserialization()