lale.lib.sklearn.select_k_best module¶

class lale.lib.sklearn.select_k_best.SelectKBest(*, score_func='<function f_classif>', k=10)¶

Select k best feature selection transformer from scikit-learn.

This documentation is auto-generated from JSON schemas.

Parameters

score_func (callable, not for optimizer, default <function f_classif at 0x7fdfbf5e3160>) – Function taking two arrays X and y, and returning a pair of arrays (scores, pvalues) or a single array with scores.
k (union type, default 10) –
Number of top features to select
- integer, >=1, >=2 for optimizer, <=’X/items/maxItems’, <=15 for optimizer
- or ‘all’

fit(X, y=None, **fit_params)¶

Train the operator.

Note: The fit method is not available until this operator is trainable.

Once this method is available, it will have the following signature:

Parameters

X (array of items : array of items : float) – Training input samples.
y (union type) –
Target values (class labels in classification, real numbers in regression).
- array of items : float
- or array of items : string
- or array of items : boolean

transform(X, y=None)¶

Transform the data.

Note: The transform method is not available until this operator is trained.

Once this method is available, it will have the following signature: