# sklearn.pipeline.make_union¶

sklearn.pipeline.make_union(*transformers, n_jobs=None, verbose=False)[source]

Construct a FeatureUnion from the given transformers.

This is a shorthand for the FeatureUnion constructor; it does not require, and does not permit, naming the transformers. Instead, they will be given names automatically based on their types. It also does not allow weighting.

Parameters
*transformerslist of estimators
n_jobsint, default=None

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

Changed in version v0.20: n_jobs default changed from 1 to None

verbosebool, default=False

If True, the time elapsed while fitting each transformer will be printed as it is completed.

Returns
fFeatureUnion

FeatureUnion
>>> from sklearn.decomposition import PCA, TruncatedSVD