sklearn.pipeline.make_pipeline()

sklearn.pipeline.make_pipeline(*steps) [source]

Construct a Pipeline from the given estimators.

This is a shorthand for the Pipeline constructor; it does not require, and does not permit, naming the estimators. Instead, their names will be set to the lowercase of their types automatically.

Returns: p : Pipeline

Examples

>>> from sklearn.naive_bayes import GaussianNB
>>> from sklearn.preprocessing import StandardScaler
>>> make_pipeline(StandardScaler(), GaussianNB(priors=None))
...     
Pipeline(steps=[('standardscaler',
                 StandardScaler(copy=True, with_mean=True, with_std=True)),
                ('gaussiannb', GaussianNB(priors=None))])

Examples using sklearn.pipeline.make_pipeline

doc_scikit_learn
2017-01-15 04:26:50
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