pmlpp/bernoulli_nb/bernoulli_nb.h

78 lines
3.1 KiB
C++

#ifndef MLPP_BERNOULLI_NB_H
#define MLPP_BERNOULLI_NB_H
/*************************************************************************/
/* bernoulli_nb.h */
/*************************************************************************/
/* This file is part of: */
/* PMLPP Machine Learning Library */
/* https://github.com/Relintai/pmlpp */
/*************************************************************************/
/* Copyright (c) 2023-present Péter Magyar. */
/* Copyright (c) 2022-2023 Marc Melikyan */
/* */
/* Permission is hereby granted, free of charge, to any person obtaining */
/* a copy of this software and associated documentation files (the */
/* "Software"), to deal in the Software without restriction, including */
/* without limitation the rights to use, copy, modify, merge, publish, */
/* distribute, sublicense, and/or sell copies of the Software, and to */
/* permit persons to whom the Software is furnished to do so, subject to */
/* the following conditions: */
/* */
/* The above copyright notice and this permission notice shall be */
/* included in all copies or substantial portions of the Software. */
/* */
/* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, */
/* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF */
/* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.*/
/* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY */
/* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, */
/* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE */
/* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */
/*************************************************************************/
#include "core/containers/hash_map.h"
#include "core/containers/vector.h"
#include "core/math/math_defs.h"
#include "core/object/reference.h"
#include "../lin_alg/mlpp_matrix.h"
#include "../lin_alg/mlpp_vector.h"
class MLPPBernoulliNB : public Reference {
GDCLASS(MLPPBernoulliNB, Reference);
public:
Ref<MLPPVector> model_set_test(const Ref<MLPPMatrix> &X);
real_t model_test(const Ref<MLPPVector> &x);
real_t score();
MLPPBernoulliNB(const Ref<MLPPMatrix> &p_input_set, const Ref<MLPPVector> &p_output_set);
MLPPBernoulliNB();
~MLPPBernoulliNB();
protected:
void compute_vocab();
void compute_theta();
void evaluate();
static void _bind_methods();
// Model Params
real_t _prior_1;
real_t _prior_0;
Vector<HashMap<real_t, int>> _theta;
Ref<MLPPVector> _vocab;
int _class_num;
// Datasets
Ref<MLPPMatrix> _input_set;
Ref<MLPPVector> _output_set;
Ref<MLPPVector> _y_hat;
};
#endif /* BernoulliNB_hpp */