32 lines
1.6 KiB
C++
32 lines
1.6 KiB
C++
// ***************************************************************
|
|
// SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez
|
|
// SPDX-FileType: SOURCE
|
|
// SPDX-License-Identifier: MIT
|
|
// ***************************************************************
|
|
|
|
#ifndef KDBLD_H
|
|
#define KDBLD_H
|
|
#include "Proposal.h"
|
|
#include "KDB.h"
|
|
|
|
namespace bayesnet {
|
|
class KDBLd : public KDB, public Proposal {
|
|
public:
|
|
explicit KDBLd(int k);
|
|
virtual ~KDBLd() = default;
|
|
KDBLd& 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;
|
|
KDBLd& 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;
|
|
KDBLd& 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 = "KDB") const override;
|
|
void setHyperparameters(const nlohmann::json& hyperparameters_) override
|
|
{
|
|
auto hyperparameters = hyperparameters_;
|
|
Proposal::setHyperparameters(hyperparameters);
|
|
KDB::setHyperparameters(hyperparameters);
|
|
}
|
|
torch::Tensor predict(torch::Tensor& X) override;
|
|
torch::Tensor predict_proba(torch::Tensor& X) override;
|
|
static inline std::string version() { return "0.0.1"; };
|
|
};
|
|
}
|
|
#endif // !KDBLD_H
|