pmlpp/mlpp/mann/mann.h
2023-01-24 19:00:54 +01:00

49 lines
1.3 KiB
C++

#ifndef MLPP_MANN_H
#define MLPP_MANN_H
//
// MANN.hpp
//
// Created by Marc Melikyan on 11/4/20.
//
#include "../hidden_layer/hidden_layer.h"
#include "../multi_output_layer/multi_output_layer.h"
#include <string>
#include <vector>
namespace MLPP {
class MANN {
public:
MANN(std::vector<std::vector<double>> inputSet, std::vector<std::vector<double>> outputSet);
~MANN();
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);
double score();
void save(std::string fileName);
void addLayer(int n_hidden, std::string activation, std::string weightInit = "Default", std::string reg = "None", double lambda = 0.5, double alpha = 0.5);
void addOutputLayer(std::string activation, std::string loss, std::string weightInit = "Default", std::string reg = "None", double lambda = 0.5, double alpha = 0.5);
private:
double Cost(std::vector<std::vector<double>> y_hat, std::vector<std::vector<double>> y);
void forwardPass();
std::vector<std::vector<double>> inputSet;
std::vector<std::vector<double>> outputSet;
std::vector<std::vector<double>> y_hat;
std::vector<HiddenLayer> network;
MultiOutputLayer *outputLayer;
int n;
int k;
int n_output;
};
} //namespace MLPP
#endif /* MANN_hpp */