Class to extract metrics from either the agent or the environment. More...
#include <classificationSelectionMetrics.h>
Public Member Functions | |
| ClassificationSelectionMetrics ()=default | |
| Default constructor. | |
| ClassificationSelectionMetrics (const std::vector< double > &scorePerClass, const std::vector< size_t > &nbEvalPerClass) | |
| Constructor with score and utility initialization. | |
| virtual const std::vector< double > & | getScorePerClass () const |
| virtual const std::vector< size_t > & | getNbEvalPerClassPerClass () const |
| void | initMetrics (const TPG::TPGVertex *agent, const Learn::LearningEnvironment &learningEnvironment) override |
| Specialization of the initialisation of the metrics. | |
| void | extractMetricsEpisode (const TPG::TPGVertex *agent, size_t nbStepsExecuted, const Learn::LearningEnvironment &learningEnvironment) override |
| Specialization of the extraction of the metrics at the end of an episode. | |
| virtual void | weightedSum (std::shared_ptr< SelectionMetrics > other, size_t nbEvaluation, size_t nbEvaluationOther) override |
| Specialization of weightedSum method to add the score per class and nbEvalPerClass. | |
 Public Member Functions inherited from Selector::SelectionMetrics | |
| SelectionMetrics ()=default | |
| Default constructor. | |
| virtual | ~SelectionMetrics ()=default |
| Default destructor. | |
| SelectionMetrics (double score, double utility=0) | |
| Constructor with score and utility initialization. | |
| virtual double | getScore () const |
| virtual double | getUtility () const |
| virtual void | extractMetricsStep (const TPG::TPGVertex *agent, std::vector< double > actionValues, const Learn::LearningEnvironment &learningEnvironment) |
| Extract metrics from the agent in the learning environment. | |
Protected Attributes | |
| std::vector< double > | scorePerClass |
| Vector storing a double score per class (i.e. per Action) of a classification LearningEnvironment. | |
| std::vector< size_t > | nbEvalPerClass |
| Vector storing a size_t value per class representing the number of evaluation per class. | |
| Protected Attributes inherited from Selector::SelectionMetrics | |
| double | score = 0 |
| double | utility = 0 |
Additional Inherited Members | |
| Static Public Member Functions inherited from Selector::SelectionMetrics | |
| template<class T > | |
| static T | weightedSum (T value, T valueOther, size_t nbEvaluation, size_t nbEvaluationOther) |
| Perform a weighted sum between 2 values. | |
Detailed Description
Class to extract metrics from either the agent or the environment.
This metrics can be used to specify the selection of the selector. This class does not implement any metrics, it need to be override by the different selection methods.
Constructor & Destructor Documentation
◆ ClassificationSelectionMetrics()
|
inline |
Constructor with score and utility initialization.
- Parameters
-
[in] scorePerClass the vector of score obtained by the agent per class. [in] nbEvalPerClass the vector of number of evaluation per class.
Member Function Documentation
◆ extractMetricsEpisode()
|
overridevirtual |
Specialization of the extraction of the metrics at the end of an episode.
Reimplemented from Selector::SelectionMetrics.
◆ getNbEvalPerClassPerClass()
|
virtual |
Return the number of evaluation per class of the agent.
◆ getScorePerClass()
|
virtual |
Return the score per class of the agent.
◆ initMetrics()
|
overridevirtual |
Specialization of the initialisation of the metrics.
Copyright or © or Copr. IETR/INSA - Rennes (2025) :
Quentin Vacher qvach.nosp@m.er@i.nosp@m.nsa-r.nosp@m.enne.nosp@m.s.fr (2025)
GEGELATI is an open-source reinforcement learning framework for training artificial intelligence based on Tangled Program Graphs (TPGs).
This software is governed by the CeCILL-C license under French law and abiding by the rules of distribution of free software. You can use, modify and/ or redistribute the software under the terms of the CeCILL-C license as circulated by CEA, CNRS and INRIA at the following URL "http://www.cecill.info".
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Reimplemented from Selector::SelectionMetrics.
◆ weightedSum()
|
overridevirtual |
Specialization of weightedSum method to add the score per class and nbEvalPerClass.
Reimplemented from Selector::SelectionMetrics.
The documentation for this class was generated from the following files:
- D:/a/gegelati/gegelati/gegelatilib/include/selector/classificationSelectionMetrics.h
- D:/a/gegelati/gegelati/gegelatilib/src/selector/classificationSelectionMetrics.cpp
