Add tests for Classifier class
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@@ -75,11 +75,11 @@ namespace bayesnet {
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if (torch::is_floating_point(dataset)) {
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throw std::invalid_argument("dataset (X, y) must be of type Integer");
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}
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if (n != features.size()) {
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throw std::invalid_argument("Classifier: X " + std::to_string(n) + " and features " + std::to_string(features.size()) + " must have the same number of features");
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if (dataset.size(0) - 1 != features.size()) {
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throw std::invalid_argument("Classifier: X " + std::to_string(dataset.size(0) - 1) + " and features " + std::to_string(features.size()) + " must have the same number of features");
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}
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if (states.find(className) == states.end()) {
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throw std::invalid_argument("className not found in states");
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throw std::invalid_argument("class name not found in states");
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}
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for (auto feature : features) {
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if (states.find(feature) == states.end()) {
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@@ -175,9 +175,9 @@ namespace bayesnet {
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{
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return model.topological_sort();
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}
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void Classifier::dump_cpt() const
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std::string Classifier::dump_cpt() const
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{
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model.dump_cpt();
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return model.dump_cpt();
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}
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void Classifier::setHyperparameters(const nlohmann::json& hyperparameters)
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{
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@@ -30,7 +30,7 @@ namespace bayesnet {
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std::vector<std::string> show() const override;
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std::vector<std::string> topological_order() override;
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std::vector<std::string> getNotes() const override { return notes; }
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void dump_cpt() const override;
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std::string dump_cpt() const override;
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void setHyperparameters(const nlohmann::json& hyperparameters) override; //For classifiers that don't have hyperparameters
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protected:
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bool fitted;
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