bigframes.ml.preprocessing#

Transformers that prepare data for other estimators. This module is styled after scikit-learns preprocessing module: https://scikit-learn.org/stable/modules/preprocessing.html.

Classes

`KBinsDiscretizer`([n_bins,strategy])	Bin continuous data into intervals.
`LabelEncoder`([min_frequency,max_categories])	Encode target labels with value between 0 and n_classes-1.
`MaxAbsScaler`()	Scale each feature by its maximum absolute value.
`MinMaxScaler`()	Transform features by scaling each feature to a given range.
`OneHotEncoder`([drop,min_frequency,...])	Encode categorical features as a one-hot format.
`PolynomialFeatures`([degree])	Generate polynomial and interaction features.
`StandardScaler`()	Standardize features by removing the mean and scaling to unit variance.

bigframes.ml.pipeline.Pipeline

bigframes.ml.preprocessing.KBinsDiscretizer