pmlpp/mlpp/lin_reg/lin_reg.h

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#ifndef MLPP_LIN_REG_H
#define MLPP_LIN_REG_H
//
// LinReg.hpp
//
// Created by Marc Melikyan on 10/2/20.
//
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#include "core/math/math_defs.h"
#include <string>
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#include <vector>
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class MLPPLinReg {
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public:
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MLPPLinReg(std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet, std::string reg = "None", real_t lambda = 0.5, real_t alpha = 0.5);
std::vector<real_t> modelSetTest(std::vector<std::vector<real_t>> X);
real_t modelTest(std::vector<real_t> x);
void NewtonRaphson(real_t learning_rate, int max_epoch, bool UI);
void gradientDescent(real_t learning_rate, int max_epoch, bool UI = 1);
void SGD(real_t learning_rate, int max_epoch, bool UI = 1);
void Momentum(real_t learning_rate, int max_epoch, int mini_batch_size, real_t gamma, bool UI = 1);
void NAG(real_t learning_rate, int max_epoch, int mini_batch_size, real_t gamma, bool UI = 1);
void Adagrad(real_t learning_rate, int max_epoch, int mini_batch_size, real_t e, bool UI = 1);
void Adadelta(real_t learning_rate, int max_epoch, int mini_batch_size, real_t b1, real_t e, bool UI = 1);
void Adam(real_t learning_rate, int max_epoch, int mini_batch_size, real_t b1, real_t b2, real_t e, bool UI = 1);
void Adamax(real_t learning_rate, int max_epoch, int mini_batch_size, real_t b1, real_t b2, real_t e, bool UI = 1);
void Nadam(real_t learning_rate, int max_epoch, int mini_batch_size, real_t b1, real_t b2, real_t e, bool UI = 1);
void MBGD(real_t learning_rate, int max_epoch, int mini_batch_size, bool UI = 1);
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void normalEquation();
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real_t score();
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void save(std::string fileName);
private:
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real_t Cost(std::vector<real_t> y_hat, std::vector<real_t> y);
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std::vector<real_t> Evaluate(std::vector<std::vector<real_t>> X);
real_t Evaluate(std::vector<real_t> x);
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void forwardPass();
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std::vector<std::vector<real_t>> inputSet;
std::vector<real_t> outputSet;
std::vector<real_t> y_hat;
std::vector<real_t> weights;
real_t bias;
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int n;
int k;
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// Regularization Params
std::string reg;
int lambda;
int alpha; /* This is the controlling param for Elastic Net*/
};
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#endif /* LinReg_hpp */