wildboar.linear_model._transform#

Module Contents#

Classes#

BaseTransformEstimator

Base class for all estimators in scikit-learn.

TransformClassifierMixin

TransformRegressorMixin

TransformRidgeCV

Mixin class for all regression estimators in scikit-learn.

TransformRidgeClassifierCV

Mixin class for all classifiers in scikit-learn.
class wildboar.linear_model._transform.BaseTransformEstimator(*, random_state=None, n_jobs=None)[source]#

Bases: wildboar.base.BaseEstimator

Base class for all estimators in scikit-learn.

Notes

All estimators should specify all the parameters that can be set at the class level in their __init__ as explicit keyword arguments (no *args or **kwargs).

fit(x, y, sample_weight=None)[source]#
class wildboar.linear_model._transform.TransformClassifierMixin[source]#
property classes_[source]#
decision_function(x)[source]#
predict(x)[source]#
predict_log_proba(x)[source]#
predict_proba(x)[source]#
class wildboar.linear_model._transform.TransformRegressorMixin[source]#
decision_function(x)[source]#
predict(x)[source]#
class wildboar.linear_model._transform.TransformRidgeCV(*, alphas=(0.1, 1.0, 10.0), fit_intercept=True, normalize=False, scoring=None, cv=None, gcv_mode=None, n_jobs=None, random_state=None)[source]#

Bases: sklearn.base.RegressorMixin, TransformRegressorMixin, BaseTransformEstimator

Mixin class for all regression estimators in scikit-learn.

class wildboar.linear_model._transform.TransformRidgeClassifierCV(*, alphas=(0.1, 1.0, 10.0), fit_intercept=True, normalize='deprecated', scoring=None, cv=None, class_weight=None, n_jobs=None, random_state=None)[source]#

Bases: sklearn.base.ClassifierMixin, TransformClassifierMixin, BaseTransformEstimator

Mixin class for all classifiers in scikit-learn.

predict_proba(x)[source]#