2023-01-23 21:13:26 +01:00
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//
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// AutoEncoder.hpp
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//
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// Created by Marc Melikyan on 11/4/20.
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//
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2023-01-24 18:52:45 +01:00
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#ifndef MLPP_AUTO_ENCODER_H
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#define MLPP_AUTO_ENCODER_H
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2023-01-23 21:13:26 +01:00
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#include <vector>
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#include <tuple>
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#include <string>
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namespace MLPP {
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class AutoEncoder{
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public:
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AutoEncoder(std::vector<std::vector<double>> inputSet, int n_hidden);
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std::vector<std::vector<double>> modelSetTest(std::vector<std::vector<double>> X);
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std::vector<double> modelTest(std::vector<double> x);
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void gradientDescent(double learning_rate, int max_epoch, bool UI = 1);
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void SGD(double learning_rate, int max_epoch, bool UI = 1);
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void MBGD(double learning_rate, int max_epoch, int mini_batch_size, bool UI = 1);
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double score();
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void save(std::string fileName);
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private:
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double Cost(std::vector<std::vector<double>> y_hat, std::vector<std::vector<double>> y);
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std::vector<std::vector<double>> Evaluate(std::vector<std::vector<double>> X);
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std::tuple<std::vector<std::vector<double>>, std::vector<std::vector<double>>> propagate(std::vector<std::vector<double>> X);
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std::vector<double> Evaluate(std::vector<double> x);
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std::tuple<std::vector<double>, std::vector<double>> propagate(std::vector<double> x);
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void forwardPass();
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std::vector<std::vector<double>> inputSet;
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std::vector<std::vector<double>> y_hat;
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std::vector<std::vector<double>> weights1;
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std::vector<std::vector<double>> weights2;
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std::vector<double> bias1;
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std::vector<double> bias2;
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std::vector<std::vector<double>> z2;
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std::vector<std::vector<double>> a2;
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int n;
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int k;
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int n_hidden;
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};
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}
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#endif /* AutoEncoder_hpp */
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