svc.hpp

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#ifndef SVC_HPP
#define SVC_HPP
 
#include <algorithm>
#include <random>
#include <vector>
 
namespace gpmp {
 
namespace ml {
 
class SVC {
  public:
    SVC(double C_ = 1.0,
        double l_rate = 0.01,
        int max_iters = 1000,
        double tol = 1e-4);
 
    void fit(const std::vector<std::vector<double>> &X_train,
             const std::vector<int> &y_train);
 
    std::vector<int> predict(const std::vector<std::vector<double>> &X_test);
 
    std::vector<double>
    predict_proba(const std::vector<std::vector<double>> &X_test);
 
    double score(const std::vector<std::vector<double>> &X_test,
                 const std::vector<int> &y_test);
 
    void set_kernel(const std::string &k_type);
 
    void set_kernel_parameters(double k_param);
 
    void set_random_state(int seed);
 
    void set_verbose(bool vbose);
 
    void set_penalty(const std::string &p_type);
 
    double cross_val_score(const std::vector<std::vector<double>> &X,
                           const std::vector<int> &y,
                           int cv = 5);
 
    std::vector<double> grid_search(const std::vector<std::vector<double>> &X,
                                    const std::vector<int> &y,
                                    const std::vector<double> &C_values,
                                    const std::vector<double> &kernel_params,
                                    int cv = 5);
 
    double C;
    double learning_rate;
    int max_iterations;
    double tolerance;
    std::string kernel_type;
    double kernel_param;
    int random_state;
    bool verbose;
    std::string penalty_type;
    std::vector<double> weights;
    double bias;
 
    double hinge_loss(double prediction, int label);
 
    double compute_loss(const std::vector<std::vector<double>> &X,
                        const std::vector<int> &y);
 
    void update_weights(const std::vector<std::vector<double>> &X,
                        const std::vector<int> &y);
 
    double kernel(const std::vector<double> &x1, const std::vector<double> &x2);
 
    double dot_product(const std::vector<double> &x1,
                       const std::vector<double> &x2);
 
    double sigmoid(double z);
 
    std::vector<int> k_fold_indices(int num_instances, int k);
 
    double accuracy(const std::vector<int> &predictions,
                    const std::vector<int> &labels);
};
 
} // namespace ml
} // namespace gpmp
 
#endif