bayes_net.hpp

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 * Copyright (C) Akiel Aries, <akiel@akiel.org>, et al.
 *
 * This software is licensed as described in the file LICENSE, which
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 * among other details are referenced in the official documentation
 * seen here : https://akielaries.github.io/openGPMP/ along with
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 * WARRANTY OF ANY KIND, either express or implied.
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#ifndef BNN_HPP
#define BNN_HPP
 
#include <cmath>
#include <random>
#include <vector>
 
class BNN {
  public:
    BNN(int input_size,
        int hidden_size,
        int output_size,
        double prior_variance = 1.0);
 
    void fit(const std::vector<std::vector<double>> &X_train,
             const std::vector<std::vector<double>> &y_train,
             int epochs = 1000);
 
    std::vector<double> predict(const std::vector<double> &input_vector);
 
    int input_size;
 
    int hidden_size;
 
    int output_size;
 
    double prior_variance;
 
    std::vector<std::vector<double>> input_to_hidden_weights;
 
    std::vector<double> hidden_biases;
 
    std::vector<std::vector<double>> hidden_to_output_weights;
 
    std::vector<double> output_biases;
 
    std::mt19937 rng;
 
    double activation_function(double x);
 
    double prior_log_likelihood();
 
    double log_likelihood(const std::vector<std::vector<double>> &X,
                          const std::vector<std::vector<double>> &y);
 
    double compute_loss(const std::vector<std::vector<double>> &X,
                        const std::vector<std::vector<double>> &y);
 
    void update_weights(const std::vector<std::vector<double>> &X,
                        const std::vector<std::vector<double>> &y,
                        double learning_rate);
};
 
#endif