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
- 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.
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())])