- 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.
- *transformerslist of estimators
One or more estimators.
- n_jobsint, default=None
Number of jobs to run in parallel.
Nonemeans 1 unless in a
-1means using all processors. See Glossary for more details.
Changed in version v0.20:
n_jobsdefault changed from 1 to None.
- verbosebool, default=False
If True, the time elapsed while fitting each transformer will be printed as it is completed.
FeatureUnionobject for concatenating the results of multiple transformer objects.
Class for concatenating the results of multiple transformer objects.
>>> from sklearn.decomposition import PCA, TruncatedSVD >>> from sklearn.pipeline import make_union >>> make_union(PCA(), TruncatedSVD()) FeatureUnion(transformer_list=[('pca', PCA()), ('truncatedsvd', TruncatedSVD())])