Hi Satra.
Can you explain the use-case a bit more?
I don't understand it from the code, sorry.
Cheers,
Andy
On 11/09/2011 04:51 PM, Satrajit Ghosh wrote:
> i often find myself doing the following for cross-validation. i.e.
> estimating the transform from the training set. would this be useful
> as a parameter on cross_val_score, gridsearchcv, etc.,. if so i'll
> send a pr.
>
> ----
> class NoTransform():
> def fit(self, X):
> return self
> def transform(self, X):
> return X
>
> def doCV(clf, X, y, Tx, cvf):
> result = []
> for train, test in cvf:
> if Tx is None:
> T = NoTransform()
> else:
> T = Tx()
> result.append((y1[test],
> clf.fit(T.fit(X[train]).transform(X[train]),
> y[train]).predict(T.transform(X[test]))
> ))
> return result
> ----
>
> cheers,
>
> satra
>
>
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