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TEST6d6eb9f0besklearn.pipeline.FeatureUnion(pca=sklearn.decomposition._truncated_svd.TruncatedSVD,fs=sklearn.feature_selection._univariate_selection.SelectPercentile)

TEST6d6eb9f0besklearn.pipeline.FeatureUnion(pca=sklearn.decomposition._truncated_svd.TruncatedSVD,fs=sklearn.feature_selection._univariate_selection.SelectPercentile)

Visibility: public Uploaded 15-01-2024 by Continuous Integration sklearn==1.3.2 numpy>=1.17.3 scipy>=1.5.0 joblib>=1.1.1 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, removed by setting to 'drop' or disabled by setting to 'passthrough' (features are passed without transformation).

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