[scikit-learn] Why is subset invariance necessary for transfom()?

necessary for cross validation. The batch versions should be preferred, although as it stands, the pointwise versions are. Thanks Charles Pehlivanian ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

[scikit-learn] Why is subset invariance necessary for transfom()?

rm" means. Joel On Tue., 21 Jan. 2020, 11:50 am Charles Pehlivanian, https://mail.python.org/mailman/listinfo/scikit-learn>> wrote: >* Not all data transformers have a transform method. For those that do, *>* subset invariance is assumed as expressed *>* in check_methods_subset_i

Re: [scikit-learn] Why is subset invariance necessary for transfom()?

see to make it pass tests is to enclose it in a loop as above. That's what I see at least. On Tue, Jan 21, 2020 at 8:35 PM Andreas Mueller wrote: > > > On 1/21/20 8:23 PM, Charles Pehlivanian wrote: > > I understand - I'm kind of conflating the idea of data sample with

Re: [scikit-learn] Why is subset invariance necessary for transfom()?

1, 2020 at 9:19 PM Charles Pehlivanian < pehlivanianchar...@gmail.com> wrote: > This is what I thought we usually do. It looks like you said we are > doing a greedy transform. > I'm not sure I follow that. In particular for spectral embedding for > example there