[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)` (l

Re: [scikit-learn] KNeighborsClassifier and metric='precomputed'

If I understood, each row of the input matrix in the predict method contains the distances from a query point to each point in the training set. I think the reference should make this more clear. 2017-01-03 15:31 GMT-02:00 federico vaggi : > That would be most helpful. Maybe also explain the log

Re: [scikit-learn] KNeighborsClassifier and metric='precomputed'

That would be most helpful. Maybe also explain the logic? On Tue, 3 Jan 2017 at 18:19 Andy wrote: > Should probably be called n_samples_train? > > > On 01/02/2017 04:10 PM, Joel Nothman wrote: > > n_indexed means the number of samples in the X passed to fit. It needs to > be able to compare eac

Re: [scikit-learn] KNeighborsClassifier and metric='precomputed'

Should probably be called n_samples_train? On 01/02/2017 04:10 PM, Joel Nothman wrote: n_indexed means the number of samples in the X passed to fit. It needs to be able to compare each prediction sample with each training sample. On 3 January 2017 at 07:44, Pedro Pazzini

Re: [scikit-learn] KNeighborsClassifier and metric='precomputed'

Joel, Your explanation helped me understand it. Thanks! 2017-01-02 19:10 GMT-02:00 Joel Nothman : > n_indexed means the number of samples in the X passed to fit. It needs to > be able to compare each prediction sample with each training sample. > > On 3 January 2017 at 07:44, Pedro Pazzini wr