# LCOV - BayesNet Coverage Report - bayesnet/ensembles/AODE.cc

LCOV - code coverage report

Current view: | top level - bayesnet/ensembles - AODE.cc (source / functions) |  |  | Coverage | Total | Hit
Test: | BayesNet Coverage Report |  | Lines: | 100.0 % | 20 | 20
Test Date: | 2024-05-06 17:54:04 |  | Functions: | 100.0 % | 4 | 4
Legend: | Lines: hit not hit |

                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              : #include "AODE.h"
           8              :
           9              : namespace bayesnet {
          10           76 :     AODE::AODE(bool predict_voting) : Ensemble(predict_voting)
          11              :     {
          12          152 :         validHyperparameters = { "predict_voting" };
          13              :
          14          228 :     }
          15            4 :     void AODE::setHyperparameters(const nlohmann::json& hyperparameters_)
          16              :     {
          17            4 :         auto hyperparameters = hyperparameters_;
          18            4 :         if (hyperparameters.contains("predict_voting")) {
          19            4 :             predict_voting = hyperparameters["predict_voting"];
          20            4 :             hyperparameters.erase("predict_voting");
          21              :         }
          22            4 :         Classifier::setHyperparameters(hyperparameters);
          23            4 :     }
          24           24 :     void AODE::buildModel(const torch::Tensor& weights)
          25              :     {
          26           24 :         models.clear();
          27           24 :         significanceModels.clear();
          28          188 :         for (int i = 0; i < features.size(); ++i) {
          29          164 :             models.push_back(std::make_unique<SPODE>(i));
          30              :         }
          31           24 :         n_models = models.size();
          32           24 :         significanceModels = std::vector<double>(n_models, 1.0);
          33           24 :     }
          34            4 :     std::vector<std::string> AODE::graph(const std::string& title) const
          35              :     {
          36            4 :         return Ensemble::graph(title);
          37              :     }
          38              : }

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