Re: [scikit-learn] modifying CV score

Well, it returns the equivalent of lambda estimator, X, y: estimator.score(X, y) On 5 January 2017 at 08:47, Jonathan Taylor wrote: > (Think this is right reply to from a digest... If not, apologies) > > Thanks for the pointers. From what I read on the API, I

[scikit-learn] modifying CV score

(Think this is right reply to from a digest... If not, apologies) Thanks for the pointers. From what I read on the API, I gather that for an estimator with a score method, inside GridSearchCV there will be pseudo-code like ... estimator.fit(X_train, y_train) scorer = estimator.score

Re: [scikit-learn] modifying CV score

You can indeed derive from BaseEstimator and implement fit, predict and optionally score. Here is the documentation for the expected estimator API: http://scikit-learn.org/stable/developers/contributing.html#apis-of-scikit-learn-objects As this is a linear regression model, you can also want to

[scikit-learn] modifying CV score

I'm looking for a simple way to get a small pipeline for choosing a parameter using a modification of CV for regression type problems. The modification is pretty simple, so, for squared-error or logistic deviance, it is a simple modification of the score of `Y` (binary labels) and `X.dot(beta)`