module Numo
  module Liblinear
    module SolverType
      L2R_LR: Integer
      L2R_L2LOSS_SVC_DUAL: Integer
      L2R_L2LOSS_SVC: Integer
      L2R_L1LOSS_SVC_DUAL: Integer
      MCSVM_CS: Integer
      L1R_L2LOSS_SVC: Integer
      L1R_LR: Integer
      L2R_LR_DUAL: Integer
      L2R_L2LOSS_SVR: Integer
      L2R_L2LOSS_SVR_DUAL: Integer
      L2R_L1LOSS_SVR_DUAL: Integer
      ONECLASS_SVM: Integer
    end

    LIBLINEAR_VERSION: Integer
    VERSION: String

    type model = {
      nr_class: Integer,
      nr_feature: Integer,
      w: Numo::DFloat,
      label: Numo::Int32,
      bias: Float,
      rho: Float
    }

    type param = {
      solver_type: Integer?,
      eps: Float?,
      C: Float?,
      nr_weight: Integer?,
      weight_label: Numo::Int32?,
      weight: Numo::DFloat?,
      p: Float?,
      nu: Float?,
      verbose: bool?,
      random_seed: Integer?
    }

    def self?.cv: (Numo::DFloat x, Numo::DFloat y, param, Integer n_folds) -> Numo::DFloat
    def self?.train: (Numo::DFloat x, Numo::DFloat y, param) -> model
    def self?.predict: (Numo::DFloat x, param, model) -> Numo::DFloat
    def self?.predict_proba: (Numo::DFloat x, param, model) -> Numo::DFloat
    def self?.decision_function: (Numo::DFloat x, param, model) -> Numo::DFloat
    def self?.save_model: (String filename, param, model) -> bool
    def self?.load_model: (String filename) -> [param, model]
  end
end