mirror of
https://github.com/Relintai/pmlpp.git
synced 2024-12-22 15:06:47 +01:00
56 lines
2.5 KiB
C++
56 lines
2.5 KiB
C++
|
|
#ifndef MLPP_UTILITIES_H
|
|
#define MLPP_UTILITIES_H
|
|
|
|
//
|
|
// Utilities.hpp
|
|
//
|
|
// Created by Marc Melikyan on 1/16/21.
|
|
//
|
|
|
|
#include <string>
|
|
#include <tuple>
|
|
#include <vector>
|
|
|
|
|
|
class Utilities {
|
|
public:
|
|
// Weight Init
|
|
static std::vector<double> weightInitialization(int n, std::string type = "Default");
|
|
static double biasInitialization();
|
|
|
|
static std::vector<std::vector<double>> weightInitialization(int n, int m, std::string type = "Default");
|
|
static std::vector<double> biasInitialization(int n);
|
|
|
|
// Cost/Performance related Functions
|
|
double performance(std::vector<double> y_hat, std::vector<double> y);
|
|
double performance(std::vector<std::vector<double>> y_hat, std::vector<std::vector<double>> y);
|
|
|
|
// Parameter Saving Functions
|
|
void saveParameters(std::string fileName, std::vector<double> weights, double bias, bool app = 0, int layer = -1);
|
|
void saveParameters(std::string fileName, std::vector<double> weights, std::vector<double> initial, double bias, bool app = 0, int layer = -1);
|
|
void saveParameters(std::string fileName, std::vector<std::vector<double>> weights, std::vector<double> bias, bool app = 0, int layer = -1);
|
|
|
|
// Gradient Descent related
|
|
static void UI(std::vector<double> weights, double bias);
|
|
static void UI(std::vector<double> weights, std::vector<double> initial, double bias);
|
|
static void UI(std::vector<std::vector<double>>, std::vector<double> bias);
|
|
static void CostInfo(int epoch, double cost_prev, double Cost);
|
|
|
|
static std::vector<std::vector<std::vector<double>>> createMiniBatches(std::vector<std::vector<double>> inputSet, int n_mini_batch);
|
|
static std::tuple<std::vector<std::vector<std::vector<double>>>, std::vector<std::vector<double>>> createMiniBatches(std::vector<std::vector<double>> inputSet, std::vector<double> outputSet, int n_mini_batch);
|
|
static std::tuple<std::vector<std::vector<std::vector<double>>>, std::vector<std::vector<std::vector<double>>>> createMiniBatches(std::vector<std::vector<double>> inputSet, std::vector<std::vector<double>> outputSet, int n_mini_batch);
|
|
|
|
// F1 score, Precision/Recall, TP, FP, TN, FN, etc.
|
|
std::tuple<double, double, double, double> TF_PN(std::vector<double> y_hat, std::vector<double> y); //TF_PN = "True", "False", "Positive", "Negative"
|
|
double recall(std::vector<double> y_hat, std::vector<double> y);
|
|
double precision(std::vector<double> y_hat, std::vector<double> y);
|
|
double accuracy(std::vector<double> y_hat, std::vector<double> y);
|
|
double f1_score(std::vector<double> y_hat, std::vector<double> y);
|
|
|
|
private:
|
|
};
|
|
|
|
|
|
#endif /* Utilities_hpp */
|