A post-processor to adjust probability to fairness between groups. More...
#include <FairnessPostProcessor.h>
Inheritance diagram for FairnessPostProcessor:
Public Member Functions | |
| void | init_post_processor (MedModel &mdl) |
| void | parse_constrains (const string &s) |
| parses the constrains | |
| 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. | |
| int | init (map< string, string > &mapper) |
| Global init for general args in all explainers. | |
| void | Learn (const MedFeatures &matrix) |
| Learns from predictor and train_matrix (PostProcessor API) | |
| void | Apply (MedFeatures &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 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 ¶m) |
| 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 | feature_name |
| feautre name to search in matrix created by model_json to generate group for fairness | |
| string | model_json |
| model json path - important for learn | |
| float | reference_group_val = MED_MAT_MISSING_VALUE |
| the value for the feature used as refernce group for fairness | |
| Fairness_Target_Type | fairness_target_type |
| fairness target - SENS of SPEC | |
| vector< Cutoff_Constraint > | constraints |
| list of constraints cutoffs. Init with comma seperated list for each constraint. The type is prefix with ":". For example Score: PR: SENS: | |
| double | resulotion = 0.1 |
| resulotion for target matching. effect speed/accuracy | |
| double | allow_distance_score = 1.0 |
| max distance allow between score | |
| double | allow_distance_target = 5.0 |
| max distance allow between target | |
| double | allow_distance_cutoff_constraint = 1.0 |
| max distance allow between constraint | |
| int | score_bin_count = 5000 |
| how much bins for score. 0 means no binning | |
| float | score_resulotion = 0 |
| if >0 will apply score resulotion for speedup | |
| MedPidRepository * | p_rep |
| required for building model for generating model (set by process) | |
| MedModel | group_feature_gen_model |
| model for generating features for priors (set in learn) | |
| string | resolved_name |
| resolved feature name (value is set after learn) | |
| 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 PostProcessor | |
| static PostProcessor * | make_processor (const string &processor_name, const string ¶ms="") |
| static PostProcessor * | make_processor (PostProcessorTypes type, const string ¶ms="") |
| static PostProcessor * | create_processor (string ¶ms) |
Detailed Description
A post-processor to adjust probability to fairness between groups.
The calibration will fit between constraints thresholds linear transformation A*X+B, to optimize some value The constraint will reduce 1 degree of freedom from the equation.
Member Function Documentation
◆ Apply()
|
virtual |
Reimplemented from PostProcessor.
◆ dprint()
|
virtual |
Reimplemented from PostProcessor.
◆ get_input_fields()
|
virtual |
List of fields that are used by this post_processor.
Reimplemented from PostProcessor.
◆ get_output_fields()
|
virtual |
List of fields that are being effected by this post_processor.
Options: "prediction:X", "attr:$NAME", "str_attr:$NAME", "feature:$NAME", "json"
Reimplemented from PostProcessor.
◆ init()
|
virtual |
Global init for general args in all explainers.
Reimplemented from SerializableObject.
◆ init_post_processor()
|
inlinevirtual |
Reimplemented from PostProcessor.
◆ Learn()
|
virtual |
Learns from predictor and train_matrix (PostProcessor API)
Reimplemented from PostProcessor.
The documentation for this class was generated from the following files:
- Internal/MedProcessTools/MedProcessTools/FairnessPostProcessor.h
- Internal/MedProcessTools/MedProcessTools/FairnessPostProcessor.cpp
