Class Algorithm

src/Algorithm.h:74–639

 */
template <class T1, class T2, class T3, class T4>
class Algorithm {
   public:
    int model_fit_max;        // Maximum number of iterations taken for the primary model fitting.
    int model_type;           // primary model type.
    int algorithm_type;       // algorithm type.
    int group_df = 0;         // freedom
    int sparsity_level = 0;   // Number of non-zero coefficients.
    double lambda_level = 0;  // l2 normalization coefficients.
    int max_iter;      // Maximum number of iterations taken for the splicing algorithm to converge.
    int exchange_num;  // Max exchange variable num.
    bool warm_start;  // When tuning the optimal parameter combination, whether to use the last solution as a warm start
                      // to accelerate the iterative convergence of the splicing algorithm.
    T4 *x = NULL;
    T1 *y = NULL;
    T2 beta;                  // coefficients.
    Eigen::VectorXd bd;       // sacrifices.
    T3 coef0;                 // intercept.
    double train_loss = 0.;   // train loss.
    T2 beta_init;             // initialization coefficients.
    T3 coef0_init;            // initialization intercept.
    Eigen::VectorXi A_init;   // initialization active set.
    Eigen::VectorXi I_init;   // initialization inactive set.
    Eigen::VectorXd bd_init;  // initialization bd vector.

    Eigen::VectorXi A_out;  // final active set.
    Eigen::VectorXi I_out;  // final active set.

    bool lambda_change;  // lambda_change or not.

    Eigen::VectorXi always_select;     // always select variable.
    double tau;                        // algorithm stop threshold
    int primary_model_fit_max_iter;    // The maximal number of iteration for primaty model fit
    double primary_model_fit_epsilon;  // The epsilon (threshold) of iteration for primaty model fit

    T2 beta_warmstart;   // warmstart beta.
    T3 coef0_warmstart;  // warmstart intercept.

    double effective_number;  // effective number of parameter.
    int splicing_type;        // exchange number update mathod.
    int sub_search;           // size of sub_searching in splicing
    int U_size;

    double beta_range[2] = {-DBL_MAX, DBL_MAX};

    Algorithm() = default;

    virtual ~Algorithm(){};

    Algorithm(int algorithm_type, int model_type, int max_iter = 100, int primary_model_fit_max_iter = 10,
              double primary_model_fit_epsilon = 1e-8, bool warm_start = true, int exchange_num = 5,
              Eigen::VectorXi always_select = Eigen::VectorXi::Zero(0), int splicing_type = 0, int sub_search = 0) {
        this->max_iter = max_iter;
        this->model_type = model_type;
        // this->coef0_init = 0.0;
        this->warm_start = warm_start;
        this->exchange_num = exchange_num;
        this->always_select = always_select;
        this->algorithm_type = algorithm_type;