bigframes.ml.compose.ColumnTransformer#
- class bigframes.ml.compose.ColumnTransformer(transformers: Iterable[Tuple[str, OneHotEncoder | StandardScaler | MaxAbsScaler | MinMaxScaler | KBinsDiscretizer | LabelEncoder | PolynomialFeatures | SimpleImputer | SQLScalarColumnTransformer, str | Iterable[str]]])[source]#
Applies transformers to columns of BigQuery DataFrames.
This estimator allows different columns or column subsets of the input to be transformed separately, and the features generated by each transformer will be concatenated to form a single feature space. This is useful for heterogeneous or columnar data to combine several feature extraction mechanisms or transformations into a single transformer.
- Parameters:
transformers – List of (name, transformer, columns) tuples specifying the transformer objects to be applied to subsets of the data.
Attributes
The collection of transformers as tuples of (name, transformer, column).
Methods
__init__(transformers)fit(X[, y])Fit all transformers using X.
fit_transform(X[, y])get_params([deep])Get parameters for this estimator.
to_gbq(model_name[, replace])Save the transformer as a BigQuery model.
transform(X)Transform X separately by each transformer, concatenate results.