mirror of https://github.com/Relintai/pmlpp.git
68 lines
1.2 KiB
C++
68 lines
1.2 KiB
C++
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#ifndef MLPP_GAUSSIAN_NB_H
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#define MLPP_GAUSSIAN_NB_H
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//
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// GaussianNB.hpp
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//
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// Created by Marc Melikyan on 1/17/21.
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//
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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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#include <vector>
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class MLPPGaussianNB : public Reference {
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GDCLASS(MLPPGaussianNB, Reference);
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public:
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/*
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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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int get_class_num();
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void set_class_num(const int val);
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*/
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std::vector<real_t> model_set_test(std::vector<std::vector<real_t>> X);
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real_t model_test(std::vector<real_t> 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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MLPPGaussianNB(std::vector<std::vector<real_t>> p_input_set, std::vector<real_t> p_output_set, int p_class_num);
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MLPPGaussianNB();
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~MLPPGaussianNB();
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protected:
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void evaluate();
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static void _bind_methods();
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int _class_num;
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std::vector<real_t> _priors;
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std::vector<real_t> _mu;
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std::vector<real_t> _sigma;
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std::vector<std::vector<real_t>> _input_set;
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std::vector<real_t> _output_set;
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std::vector<real_t> _y_hat;
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bool _initialized;
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};
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#endif /* GaussianNB_hpp */
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