Re: [scikit-learn] Contribution - Markov Clustering

I have, The only criterion that I am unsure about is the number citations. In the literature Markov clustering is usually compared to affinity prolongation, which also has a similar number of citations. I have attached my implementation in my github account for you to review. Do I have your appr

Re: [scikit-learn] Contribution - Markov Clustering

hi, did you have a look at : http://scikit-learn.org/stable/faq.html#what-are-the-inclusion-criteria-for-new-algorithms Alex ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

[scikit-learn] Contribution - Markov Clustering

Hi, I've been advised to contact you before working on an implementation of a new feature. I am thinking of implementing the Markov clustering and add it to sklearn.cluster module. See: https://micans.org/mcl/ https://gist.github.com/urigoren/1f76567f3af56ed8c33f076537768a60 Do you know if anyo

Re: [scikit-learn] Contribution

On Mon, Jul 10, 2017 at 04:10:09PM +, federico vaggi wrote: > There is a fantastic library called lightning where the optimization > routines are first class citizens: > http://contrib.scikit-learn.org/lightning/ - you can take a look there. > However, lightning focuses on convex optimization,

Re: [scikit-learn] Contribution

Hi, I'd like to implement the Markov clustering algorithm, Any objections? On Jul 10, 2017 7:10 PM, "federico vaggi" wrote: Hey Gurhan, sklearn doesn't really neatly separate optimizers from the models they optimize at the level of API (except in a few cases). In order to make the package mor

Re: [scikit-learn] Contribution

Hey Gurhan, sklearn doesn't really neatly separate optimizers from the models they optimize at the level of API (except in a few cases). In order to make the package more friendly to newer user, each model has excellent optimizer defaults that you can use, and only in a few cases does it make sen

Re: [scikit-learn] Contribution

Howdy This question and the one right after in the FAQ are probably relevant re: inclusion of new algorithms: http://scikit-learn.org/stable/faq.html#what-are-the-inclusion-criteria-for-new-algorithms. The gist is that we only include well established algorithms, and there are no end to those. I t

[scikit-learn] Contribution

Hi everyone, I am wondering, How can I use external optimization algorithms with scikit-learn, for instance neural network , instead of defined algorithms ( Stochastic Gradient Descent, Adam, or L-BFGS). Furtherm