regularizers.hpp

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#ifndef REGULARIZERS_HPP
#define REGULARIZERS_HPP
 
#include <vector>
 
namespace gpmp {
 
namespace ml {
 
class Regularize {
  public:
    static double l1_regularization(const std::vector<double> &weights,
                                    double lambda);
 
    static double l2_regularization(const std::vector<double> &weights,
                                    double lambda);
 
    static double elastic_net_regularization(const std::vector<double> &weights,
                                             double lambda1,
                                             double lambda2);
 
    static double dropout_regularization(double dropout_rate, int num_neurons);
 
    static bool early_stopping(double current_val_loss,
                               double &best_val_loss,
                               int patience,
                               int epoch);
 
    static std::vector<double>
    ensemble_predictions(const std::vector<std::vector<double>> &predictions);
 
    static void max_norm_regularization(std::vector<double> &weights,
                                        double max_norm);
 
    static void weight_decay_regularization(std::vector<double> &weights,
                                            double lambda);
 
    static std::vector<std::vector<double>>
    batch_normalization(const std::vector<std::vector<double>> &input_data,
                        double epsilon = 1e-5,
                        double scale = 1.0,
                        double shift = 0.0);
 
    static std::vector<std::vector<double>>
    data_augmentation(const std::vector<std::vector<double>> &input_data,
                      int augmentation_factor);
};
 
} // namespace ml
 
} // namespace gpmp
 
#endif