> I've been trying to understand how to use sklearn for this as there is > no need for me to rewrite the basic CV functions. I'd like to be able > to use my own custom estimator (so I guess I just need a subclass of > BaseEstimator with a `fit` method with (X,y) signature?), as well as my > own modification of the score.
Be aware that scikit-learn assume a few things about estimators. One of them being that the __init__ should not do anything else than store the parameters that it is given. > I'd be happy to understand the code for an estimator whose fit returns > `np.zeros(X.shape[1])` Another assumption is that "fit" always returns self. The API that defines a scikit-learn object is detailed here: http://scikit-learn.org/stable/developers/contributing.html#apis-of-scikit-learn-objects _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
