Medial Code Documentation
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Data Structures | Enumerations | Functions
PostProcessor.h File Reference
#include <vector>
#include <SerializableObject/SerializableObject/SerializableObject.h>
#include "MedSamples.h"
#include "MedModel.h"
#include "Effected_Field.h"

Go to the source code of this file.

Data Structures

class  PostProcessor
 An Abstract PostProcessor class. More...
 
class  MultiPostProcessor
 A wrapper for parallel call to post_processors group. More...
 

Enumerations

enum  PostProcessorTypes {
  FTR_POSTPROCESS_MULTI , FTR_POSTPROCESS_CALIBRATOR , FTR_POSTPROCESS_TREE_SHAP , FTR_POSTPROCESS_SHAPLEY ,
  FTR_POSTPROCESS_MISSING_SHAP , FTR_POSTPROCESS_LIME_SHAP , FTR_POSTPROCESS_KNN_EXPLAIN , FTR_POSTPROCESS_LINEAR ,
  FTR_POSTPROCESS_ITERATIVE_SET , FTR_POSTPROCESS_AGGREGATE_PREDS , FTR_POSTPROCESS_ADJUST , FTR_POSTPROCESS_FAIRNESS ,
  FTR_POSTPROCESS_LAST
}
 

Functions

PostProcessorTypes post_processor_name_to_type (const string &post_processor)
 

Enumeration Type Documentation

◆ PostProcessorTypes

Enumerator
FTR_POSTPROCESS_MULTI 

"multi_processor" or "multi" to create MultiPostProcessor

FTR_POSTPROCESS_CALIBRATOR 

"calibrator" to create Calibrator

FTR_POSTPROCESS_TREE_SHAP 

"tree_shap" to create TreeExplainer to explain tree mode or mimic generic model with trees model

FTR_POSTPROCESS_SHAPLEY 

"shapley" to create ShapleyExplainer - model agnostic shapley explainer for model. sample masks using gibbs or GAN

FTR_POSTPROCESS_MISSING_SHAP 

"missing_shap" to create MissingShapExplainer - model agnostic shapley algorithm on trained model to handle prediciton with missing values(retrains new model). much faster impl, because gibbs/GAN is not needed

FTR_POSTPROCESS_LIME_SHAP 

"lime_shap" to create LimeExplainer - model agnostic shapley algorithm with lime on shap values sampling

FTR_POSTPROCESS_KNN_EXPLAIN 

"knn" Explainer built on knn principles KNN_Explainer

FTR_POSTPROCESS_LINEAR 

"linear" to create LinearExplainer to explain linear model - importance is score change when putting zero in the feature/group of features

FTR_POSTPROCESS_ITERATIVE_SET 

"iterative_set" to create IterativeSetExplainer - model agnostic iterative explainer for model. sample masks using gibbs or GAN

FTR_POSTPROCESS_AGGREGATE_PREDS 

"aggregate_preds" to create AggregatePredsPostProcessor - averaging model predictions after resampling

FTR_POSTPROCESS_ADJUST 

"adjust_probs" to adjust model calibrated predictions according to priors. Creates ProbAdjustPostProcessor

FTR_POSTPROCESS_FAIRNESS 

"fairness_adjust" to adjust model calibrated predictions according to priors. Creates ProbAdjustPostProcessor