ml_grid.model_classes.catboostClassifier

Classes

CatBoostSKLearnWrapper

Initializes the CatBoostSKLearnWrapper.

Module Contents

class ml_grid.model_classes.catboostClassifier.CatBoostSKLearnWrapper(**kwargs: Any)[source]

Bases: sklearn.base.BaseEstimator, sklearn.base.ClassifierMixin

Initializes the CatBoostSKLearnWrapper.

Parameters:: **kwargs (Any) – Keyword arguments passed directly to the catboost.CatBoostClassifier.

model[source]

fit(X: pandas.DataFrame | numpy.ndarray, y: pandas.Series | numpy.ndarray) → CatBoostSKLearnWrapper[source]

Fits the CatBoost model.

Parameters:

X (Union[pd.DataFrame, np.ndarray]) – The training input samples.
y (Union[pd.Series, np.ndarray]) – The target values.

Returns:

The fitted estimator.

Return type:

CatBoostSKLearnWrapper

predict(X: pandas.DataFrame | numpy.ndarray) → numpy.ndarray[source]

Predicts class labels for samples in X.

Parameters:: X (Union[pd.DataFrame, np.ndarray]) – The input samples to predict.
Returns:: The predicted class labels.
Return type:: np.ndarray

predict_proba(X: pandas.DataFrame | numpy.ndarray) → numpy.ndarray[source]

Predicts class probabilities for samples in X.

Parameters:: X (Union[pd.DataFrame, np.ndarray]) – The input samples.
Returns:: The class probabilities of the input samples.
Return type:: np.ndarray