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