Re: [scikit-learn] NEP: Random Number Generator Policy

On 6/19/18 08:12, Andreas Mueller wrote: I don't think I have the bandwidth but I agree :-/ Not sure if any of the other core devs do. I can try to read it next week but that's probably too late? We're not on a deadline. If you're interested in reading the NEP and providing feedback/consent,

Re: [scikit-learn] imbalanced classes: class_weight

Hi, Have you seen http://imbalanced-learn.org? Best, Chris On Tue, 19 Jun 2018 17:53 S Hamidizade, wrote: > Hi > > I would appreciate if you could let me know what is the best way to > categorize the approaches which have been developed to deal with imbalance > class problem? > > *This

Re: [scikit-learn] NEP: Random Number Generator Policy

On Mon, Jun 18, 2018 at 11:34:38PM -0700, Robert Kern wrote: > However, I'd really appreciate it if I could get some > kind of feedback from a scikit-learn dev, I didn't read the NEP, only your summary. That said, it seems quite reasonably aligned with our practice, and hence shouldn't pose a

Re: [scikit-learn] NEP: Random Number Generator Policy

I don't think I have the bandwidth but I agree :-/ Not sure if any of the other core devs do. I can try to read it next week but that's probably too late? On 06/19/2018 02:34 AM, Robert Kern wrote: On 6/16/18 00:59, Robert Kern wrote: I have made a significant revision. In this version,

[scikit-learn] imbalanced classes: class_weight

Hi I would appreciate if you could let me know what is the best way to categorize the approaches which have been developed to deal with imbalance class problem? *This article categorizes them into:* 1. Preprocessing:

Re: [scikit-learn] NEP: Random Number Generator Policy

On 6/16/18 00:59, Robert Kern wrote: I have made a significant revision. In this version, downstream projects like scikit-learn should experience significantly less forced churn. https://github.com/rkern/numpy/blob/nep/rng-clarification/doc/neps/nep-0019-rng-policy.rst