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TEST8830ef928asklearn.pipeline.FeatureUnion(pca=sklearn.decomposition._truncated_svd.TruncatedSVD,fs=sklearn.feature_selection._univariate_selection.SelectPercentile)

TEST8830ef928asklearn.pipeline.FeatureUnion(pca=sklearn.decomposition._truncated_svd.TruncatedSVD,fs=sklearn.feature_selection._univariate_selection.SelectPercentile)

Visibility: public Uploaded 18-10-2024 by Continuous Integration sklearn==0.23.1 numpy>=1.13.3 scipy>=0.19.1 joblib>=0.11 threadpoolctl>=2.0.0 0 runs
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Concatenates results of multiple transformer objects. This estimator applies a list of transformer objects in parallel to the input data, then concatenates the results. This is useful to combine several feature extraction mechanisms into a single transformer. Parameters of the transformers may be set using its name and the parameter name separated by a '__'. A transformer may be replaced entirely by setting the parameter with its name to another transformer, or removed by setting to 'drop'.

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