Files
BayesNet/bayesnet/classifiers/TANLd.h

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C++

// ***************************************************************
// SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
// SPDX-FileType: SOURCE
// SPDX-License-Identifier: MIT
// ***************************************************************
#ifndef TANLD_H
#define TANLD_H
#include "TAN.h"
#include "Proposal.h"
namespace bayesnet {
class TANLd : public TAN, public Proposal {
private:
public:
TANLd();
virtual ~TANLd() = default;
TANLd& fit(torch::Tensor& X, torch::Tensor& y, const std::vector<std::string>& features, const std::string& className, map<std::string, std::vector<int>>& states, const Smoothing_t smoothing) override;
TANLd& fit(torch::Tensor& dataset, const std::vector<std::string>& features, const std::string& className, map<std::string, std::vector<int>>& states, const Smoothing_t smoothing) override;
TANLd& commonFit(const std::vector<std::string>& features, const std::string& className, map<std::string, std::vector<int>>& states, const Smoothing_t smoothing);
std::vector<std::string> graph(const std::string& name = "TANLd") const override;
void setHyperparameters(const nlohmann::json& hyperparameters_) override
{
auto hyperparameters = hyperparameters_;
Proposal::setHyperparameters(hyperparameters);
TAN::setHyperparameters(hyperparameters);
}
torch::Tensor predict(torch::Tensor& X) override;
torch::Tensor predict_proba(torch::Tensor& X) override;
};
}
#endif // !TANLD_H