package.common.modelCV module

class package.common.modelCV.BaseModelCV(n_splits: int = 3, n_repeats: int = 1, metric_func: Optional[Callable] = None, direction: Literal['minimize', 'maximize'] = 'maximize')

ベースクラス: ABC

abstract define_search_space(trial)

fit(X: DataFrame, Y: Series, n_trials: int = 150)

abstract property model_class

class package.common.modelCV.LGBCV(n_splits: int = 3, n_repeats: int = 1, metric_func: Optional[Callable] = None, direction: Literal['minimize', 'maximize'] = 'maximize')

ベースクラス: BaseModelCV

define_search_space(trial)

property model_class

class package.common.modelCV.LGBRCV(n_splits: int = 3, n_repeats: int = 1, metric_func: Optional[Callable] = None, direction: Literal['minimize', 'maximize'] = 'maximize')

ベースクラス: BaseModelCV

define_search_space(trial)

property model_class

class package.common.modelCV.RidgeCV(n_splits: int = 3, n_repeats: int = 1, metric_func: Optional[Callable] = None, direction: Literal['minimize', 'maximize'] = 'maximize')

ベースクラス: BaseModelCV

define_search_space(trial)

property model_class

class package.common.modelCV.SVCCV(n_splits: int = 3, n_repeats: int = 1, metric_func: Optional[Callable] = None, direction: Literal['minimize', 'maximize'] = 'maximize')

ベースクラス: BaseModelCV

define_search_space(trial)

property model_class

class package.common.modelCV.SVRCV(n_splits: int = 3, n_repeats: int = 1, metric_func: Optional[Callable] = None, direction: Literal['minimize', 'maximize'] = 'maximize')

ベースクラス: BaseModelCV

define_search_space(trial)

property model_class