FeatureUnion

Concatenates results of multiple transformer objects.

Quickstart

from sktime.transformations.compose import FeatureUnion

estimator = FeatureUnion(transformer_list, n_jobs=None, transformer_weights=None, flatten_transform_index=True)

Parameters(4)

transformer_listlist of (string, transformer) tuples

List of transformer objects to be applied to the data. The first half of each tuple is the name of the transformer.

n_jobsint or None, optional (default=None)

Number of jobs to run in parallel. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors.

transformer_weightsdict, optional

Multiplicative weights for features per transformer. Keys are transformer names, values the weights.

flatten_transform_indexbool, optional (default=True)

if True, columns of return DataFrame are flat, by “transformer__variablename” if False, columns are MultiIndex (transformer, variablename) has no effect if return mtype is one without column names