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This commit is contained in:
Ricardo Montañana Gómez
2025-02-18 11:04:24 +01:00
parent bd5ba14f04
commit 14dd8ebb66
2 changed files with 19 additions and 19 deletions
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28
src/experimental_clfs/XA1DE.h
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@@ -21,34 +21,34 @@ namespace platform {
public:
XA1DE();
virtual ~XA1DE() = default;
void setDebug(bool debug) { this->debug = debug; }
std::vector<std::vector<double>> predict_proba_threads(const std::vector<std::vector<int>>& test_data);
std::vector<std::vector<double>> predict_proba_threads(const std::vector<std::vector<int>>& test_data);
std::vector<std::vector<double>> predict_proba(std::vector<std::vector<int>>& X) override;
float score(std::vector<std::vector<int>>& X, std::vector<int>& y) override;
XA1DE& fit(std::vector<std::vector<int>>& X, std::vector<int>& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override;
XA1DE& fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override;
XA1DE& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override;
XA1DE& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing) override;
XA1DE& fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override { return *this; };
XA1DE& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const bayesnet::Smoothing_t smoothing) override { return *this; };
XA1DE& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, std::map<std::string, std::vector<int>>& states, const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing) override { return *this; };
torch::Tensor predict(torch::Tensor& X) override { return torch::zeros(0); };
std::vector<int> predict(std::vector<std::vector<int>>& X) override;
torch::Tensor predict_proba(torch::Tensor& X) override { return torch::zeros(0); };
int getNumberOfNodes() const override { return 0; };
int getNumberOfEdges() const override { return 0; };
int getNumberOfStates() const override { return 0; };
int getClassNumStates() const override { return 0; };
torch::Tensor predict(torch::Tensor& X) override { return torch::zeros(0); };
std::vector<int> predict(std::vector<std::vector<int>>& X) override;
torch::Tensor predict_proba(torch::Tensor& X) override { return torch::zeros(0); };
std::vector<std::vector<double>> predict_proba(std::vector<std::vector<int>>& X) override;
bayesnet::status_t getStatus() const override { return status; }
std::string getVersion() override { return { project_version.begin(), project_version.end() }; };
std::string getVersion() override { return version; };
float score(torch::Tensor& X, torch::Tensor& y) override { return 0; };
float score(std::vector<std::vector<int>>& X, std::vector<int>& y) override;
std::vector<std::string> show() const override { return {}; }
std::vector<std::string> topological_order() override { return {}; }
std::vector<std::string> getNotes() const override { return notes; }
std::string dump_cpt() const override { return ""; }
void setHyperparameters(const nlohmann::json& hyperparameters) override;
std::vector<std::string>& getValidHyperparameters() { return validHyperparameters; }
void setDebug(bool debug) { this->debug = debug; }
protected:
void trainModel(const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing) override;
void trainModel(const torch::Tensor& weights, const bayesnet::Smoothing_t smoothing) override {};
private:
inline void normalize_weights(int num_instances)
@@ -61,7 +61,6 @@ namespace platform {
w = w * num_instances / sum;
}
}
// The instances of the dataset
Xaode aode_;
std::vector<double> weights_;
CountingSemaphore& semaphore_;
@@ -69,6 +68,7 @@ namespace platform {
bayesnet::status_t status = bayesnet::NORMAL;
std::vector<std::string> notes;
bool use_threads = false;
std::string version = "0.9.7";
};
}
#endif // XA1DE_H