Dear expert,
I'm trying to do dimensionality reduction using 'pipeline' based on
the following:
>>> from sklearn.pipeline import Pipeline
>>> from sklearn.svm import SVC
>>> from sklearn.decomposition import PCA
>>> estimators = [('reduce_dim', PCA()), ('svm', SVC())]
>>> clf = Pipeline(estimators)
>>> clf
However I discover the AUC is no different from AUC just by using SVM alone.
I expect the dimension of X is reduced in that 'pipeline' before
passing to SVM.
Am I right?
If not what's the right way to implement that?
Thanks and hope to hear from you again.
Best,
Viswanath
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