mirror of
https://github.com/Relintai/pmlpp.git
synced 2024-12-22 15:06:47 +01:00
53 lines
1.5 KiB
C++
53 lines
1.5 KiB
C++
|
|
#ifndef MLPP_AUTO_ENCODER_H
|
|
#define MLPP_AUTO_ENCODER_H
|
|
|
|
//
|
|
// AutoEncoder.hpp
|
|
//
|
|
// Created by Marc Melikyan on 11/4/20.
|
|
//
|
|
|
|
#include <string>
|
|
#include <tuple>
|
|
#include <vector>
|
|
|
|
class MLPPAutoEncoder {
|
|
public:
|
|
MLPPAutoEncoder(std::vector<std::vector<double>> inputSet, int n_hidden);
|
|
std::vector<std::vector<double>> modelSetTest(std::vector<std::vector<double>> X);
|
|
std::vector<double> modelTest(std::vector<double> x);
|
|
void gradientDescent(double learning_rate, int max_epoch, bool UI = 1);
|
|
void SGD(double learning_rate, int max_epoch, bool UI = 1);
|
|
void MBGD(double learning_rate, int max_epoch, int mini_batch_size, bool UI = 1);
|
|
double score();
|
|
void save(std::string fileName);
|
|
|
|
private:
|
|
double Cost(std::vector<std::vector<double>> y_hat, std::vector<std::vector<double>> y);
|
|
|
|
std::vector<std::vector<double>> Evaluate(std::vector<std::vector<double>> X);
|
|
std::tuple<std::vector<std::vector<double>>, std::vector<std::vector<double>>> propagate(std::vector<std::vector<double>> X);
|
|
std::vector<double> Evaluate(std::vector<double> x);
|
|
std::tuple<std::vector<double>, std::vector<double>> propagate(std::vector<double> x);
|
|
void forwardPass();
|
|
|
|
std::vector<std::vector<double>> inputSet;
|
|
std::vector<std::vector<double>> y_hat;
|
|
|
|
std::vector<std::vector<double>> weights1;
|
|
std::vector<std::vector<double>> weights2;
|
|
|
|
std::vector<double> bias1;
|
|
std::vector<double> bias2;
|
|
|
|
std::vector<std::vector<double>> z2;
|
|
std::vector<std::vector<double>> a2;
|
|
|
|
int n;
|
|
int k;
|
|
int n_hidden;
|
|
};
|
|
|
|
#endif /* AutoEncoder_hpp */
|