ProbAdjustPostProcessor.h

#ifndef __PROBADJUSTPOSTPROCESSOR_H__
#define __PROBADJUSTPOSTPROCESSOR_H__
 
#include <MedAlgo/MedAlgo/MedAlgo.h>
#include "PostProcessor.h"
#include <Logger/Logger/Logger.h>
 
// A post-processor to adjust probability to fit given priors.
// Priors are determined according to INTEGER features generated by a model (according to priorsJson)
// the odds of the intial predictor can be learned or externally supplied, and is used in the Bayesian adjustment
 
class ProbAdjustPostProcessor : public PostProcessor {
public:
    vector<string> names;
    vector<string> resolvedNames;
    vector<int> min, max, factors;
    vector<float> probs;
    vector<float> odds ; 
    MedModel *priorsModel; 
    MedPidRepository *p_rep; 
    bool model_initiated = false;
 
    string priorsFile;
    string priorsJson;
 
    int inherited_verbosity = 0; // for priorsModel
    // Functions
    ProbAdjustPostProcessor() { processor_type = PostProcessorTypes::FTR_POSTPROCESS_ADJUST; };
    ~ProbAdjustPostProcessor() { delete priorsModel; };
    void init_post_processor(MedModel& mdl) { p_rep = mdl.p_rep; inherited_verbosity = mdl.verbosity; }
 
    void get_input_fields(vector<Effected_Field> &fields) const;
    void get_output_fields(vector<Effected_Field> &fields) const;
 
    int init(map<string, string> &mapper);
 
    void Learn(const MedFeatures &matrix);
    void Apply(MedFeatures &matrix);
 
    // Helper functions
    void readPriors();
    void getOdds(const MedFeatures &matrix);
 
    void set_model_initiated(bool val) { model_initiated = val; }
 
    ADD_CLASS_NAME(ProbAdjustPostProcessor)
    ADD_SERIALIZATION_FUNCS(processor_type, names,resolvedNames,min,max,factors,probs, priorsFile, odds, priorsModel, priorsJson)
};
 
MEDSERIALIZE_SUPPORT(ProbAdjustPostProcessor)
 
#endif