Re: [Scikit-learn-general] [ANN] scikit-learn 0.16.0 is out!

Thank you, all! Thanks, Michael J. Bommarito II, CEO Bommarito Consulting, LLC *Web:* http://www.bommaritollc.com *Mobile:* +1 (646) 450-3387 On Fri, Mar 27, 2015 at 12:33 PM, Vinayak Mehta wrote: > Cheers! > > On Fri, Mar 27, 2015 at 10:02 PM, Kyle Kastner > wrote: > >> Awesome! Congratulatio

Re: [Scikit-learn-general] GSoC2015 topics

Milton, my opinion is that the best work available in Python for clustering and community detection has been done in the igraph project ( http://igraph.org/). While I would personally love to see better support for these un- and semi-supervised taks in sklearn, it is a substantial investment of

[Scikit-learn-general] sklearn in a prediction publication with data and code

Hello all, First, of course, is a thank you to all contributors! The (pre-)publication below exists in large part due to sklearn, and would have been substantially more painful/worse without it. Second, while the paper itself is written for a less technical audience than most readers here, we

Re: [Scikit-learn-general] LabelBinarizer change between 0.14 and 0.15

Relevant to this: https://github.com/scikit-learn/scikit-learn/pull/3243 Thanks, Michael J. Bommarito II, CEO Bommarito Consulting, LLC *Web:* http://www.bommaritollc.com *Mobile:* +1 (646) 450-3387 On Wed, Jul 16, 2014 at 6:59 PM, Christian Jauvin wrote: > I can open an issue, but on the othe

Re: [Scikit-learn-general] scikit-learn 0.15.0 is out \o/

Thank you for your hard work! Enjoy the sprint! Thanks, Michael J. Bommarito II, CEO Bommarito Consulting, LLC *Web:* http://www.bommaritollc.com *Mobile:* +1 (646) 450-3387 On Tue, Jul 15, 2014 at 8:23 AM, Jeff Elmore wrote: > Thanks to everyone who helped to make it happen! > > We all appre

Re: [Scikit-learn-general] Exporting a scikit learn model

Depending on how productionized or robust you want the model to be, you might pick a language-agnostic format and wrap the fit/predict methods in a web service. A couple ideas that have worked well in various projects: For web service: 1. Flask for very light-weight, barebones implementations 2.