pmlpp/mlpp/pca/pca.h

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#ifndef MLPP_PCA_H
#define MLPP_PCA_H
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/*************************************************************************/
/* pca.h */
/*************************************************************************/
/* This file is part of: */
/* PMLPP Machine Learning Library */
/* https://github.com/Relintai/pmlpp */
/*************************************************************************/
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/* Copyright (c) 2023-present Péter Magyar. */
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/* 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. */
/*************************************************************************/
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#include "core/math/math_defs.h"
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#include "core/object/reference.h"
#include "../lin_alg/mlpp_matrix.h"
#include "../lin_alg/mlpp_vector.h"
class MLPPPCA : public Reference {
GDCLASS(MLPPPCA, Reference);
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public:
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Ref<MLPPMatrix> get_input_set();
void set_input_set(const Ref<MLPPMatrix> &val);
int get_k();
void set_k(const int val);
Ref<MLPPMatrix> principal_components();
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real_t score();
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MLPPPCA(const Ref<MLPPMatrix> &p_input_set, int p_k);
MLPPPCA();
~MLPPPCA();
protected:
static void _bind_methods();
Ref<MLPPMatrix> _input_set;
int _k;
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Ref<MLPPMatrix> _x_normalized;
Ref<MLPPMatrix> _u_reduce;
Ref<MLPPMatrix> _z;
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};
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#endif /* PCA_hpp */