Skip to main content

RandomizedSearchCV

#include <Skigen/ModelSelection>

template <typename Estimator, typename Scalar = double>
class Skigen::RandomizedSearchCV(estimator, param_distributions, n_iter=10, cv=5, refit=true, random_state=std::nullopt)

Randomised search over a parameter grid with cross-validation.

Mirrors sklearn.model_selection.RandomizedSearchCV.

Samples n_iter random parameter combinations from the supplied grid (with replacement) and evaluates each via K-fold cross-validation. Unlike GridSearchCV, only a fixed budget of combinations is tried.



Attributes:

  • best_estimator : Estimator

  • best_params : ParameterDict

  • best_score : Scalar

  • best_index : std::size_t

  • cv_results_params : const std::vector< ParameterDict > &

  • cv_results_mean_score : const std::vector< Scalar > &


Methods

fit(X, y)


predict(X)


score(X, y)