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BayesNet/html/bayesnet/feature_selection/FeatureSelect.h.gcov.html

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LCOV - code coverage report
Current view: top level - bayesnet/feature_selection - FeatureSelect.h (source / functions) Coverage Total Hit
Test: coverage.info Lines: 100.0 % 1 1
Test Date: 2024-04-21 17:30:26 Functions: 50.0 % 2 1 

            Line data    Source code
       1              : // ***************************************************************
       2              : // SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
       3              : // SPDX-FileType: SOURCE
       4              : // SPDX-License-Identifier: MIT
       5              : // ***************************************************************
       6              : 
       7              : #ifndef FEATURE_SELECT_H
       8              : #define FEATURE_SELECT_H
       9              : #include <torch/torch.h>
      10              : #include <vector>
      11              : #include "bayesnet/utils/BayesMetrics.h"
      12              : namespace bayesnet {
      13              :     class FeatureSelect : public Metrics {
      14              :     public:
      15              :         // dataset is a n+1xm tensor of integers where dataset[-1] is the y std::vector
      16              :         FeatureSelect(const torch::Tensor& samples, const std::vector<std::string>& features, const std::string& className, const int maxFeatures, const int classNumStates, const torch::Tensor& weights);
      17           22 :         virtual ~FeatureSelect() {};
      18              :         virtual void fit() = 0;
      19              :         std::vector<int> getFeatures() const;
      20              :         std::vector<double> getScores() const;
      21              :     protected:
      22              :         void initialize();
      23              :         void computeSuLabels();
      24              :         double computeSuFeatures(const int a, const int b);
      25              :         double symmetricalUncertainty(int a, int b);
      26              :         double computeMeritCFS();
      27              :         const torch::Tensor& weights;
      28              :         int maxFeatures;
      29              :         std::vector<int> selectedFeatures;
      30              :         std::vector<double> selectedScores;
      31              :         std::vector<double> suLabels;
      32              :         std::map<std::pair<int, int>, double> suFeatures;
      33              :         bool fitted = false;
      34              :     };
      35              : }
      36              : #endif

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