[Scikit-learn-general] Anaconda on tablet

Dear All,I want to install anaconda or any other version of python with all the scipy,... packages on my android tablet. Would you please give me a link to download any.Thank you-- One dashboard for servers and applicatio

Re: [Scikit-learn-general] using forkserver through GridSearchCV and friends

On Fri, May 8, 2015 at 9:40 AM, Skipper Seabold wrote: > Hi, > > Is there anyway to specify the backend used by joblib? It's not > obvious to me and this doesn't seem to work. > > from multiprocessing import set_start_method > set_start_method("forkserver") > Ah, it has to be in a `if __n

Re: [Scikit-learn-general] Contributing to scikit-learn with a re-implementation of a Random Forest based iterative feature selection method

It doesn't need to be super technical, and we try to keep the user guide "easy to understand". No bonus points for unnecessary latex ;) The example should be as illustrative and fair as possible, and built-in datasets are preferred. It shouldn't be to heavy-weight, though. If you like, you can sh

Re: [Scikit-learn-general] Contributing to scikit-learn with a re-implementation of a Random Forest based iterative feature selection method

Hi Andy, Thanks! Will definitely do a github pull request once Miron confirmed he benchmarked my implementation by running it on the datasets the method was published with. I wrote a blog post about it, which explains the differences but in a quite casual an non rigorous way: http://danielh

Re: [Scikit-learn-general] Contributing to scikit-learn with a re-implementation of a Random Forest based iterative feature selection method

Btw, an example that compares this against existing feature selection methods that explains differences and advantages would help users and convince us to merge ;) On 05/08/2015 02:34 PM, Daniel Homola wrote: Hi all, I wrote a couple of weeks ago about implementing the Boruta all-relevant f

Re: [Scikit-learn-general] Contributing to scikit-learn with a re-implementation of a Random Forest based iterative feature selection method

Hi Daniel. That looks cool. Can you do a github pull request? See the contributor docs: http://scikit-learn.org/dev/developers/index.html Thanks, Andy On 05/08/2015 02:34 PM, Daniel Homola wrote: Hi all, I wrote a couple of weeks ago about implementing the Boruta all-relevant feature selectio

Re: [Scikit-learn-general] Contributing to scikit-learn with a re-implementation of a Random Forest based iterative feature selection method

Hi all, I wrote a couple of weeks ago about implementing the Boruta all-relevant feature selection method algorithm in Python.. I think it's ready to go now. I wrote fit, transform and fit_transform methods for it to make it sklearn like. Here it is: https://bitbucket.org/danielhomola/borut

Re: [Scikit-learn-general] use features from a sklearn branch

Otherwise maybe you can try to make a new branch on your scikit and copy this repo on it... Nicolas On 8 May 2015 9:34 am, "Artem" wrote: > Looks like you have a circular import, and Python doesn't like them. > Sorry, I don't have a quick hack solution to this, all I can propose is to > look at i

Re: [Scikit-learn-general] Get Other Classification Metrics For GridSearch

Hi Adam. You can get the f_score by setting ``GridSearchCV(..., scoring='f1_score')``. By default, the "positive" class if the one labeled "1": http://scikit-learn.org/dev/modules/generated/sklearn.metrics.f1_score.html#sklearn.metrics.f1_score If you want more control, you can do my_f_scoring

Re: [Scikit-learn-general] use features from a sklearn branch

Looks like you have a circular import, and Python doesn't like them. Sorry, I don't have a quick hack solution to this, all I can propose is to look at import chain, understand, which import breaks it all, and get rid of it. For example, you can move some imports into functions, so they're not call

[Scikit-learn-general] use features from a sklearn branch

Hi, due to my need for a good isolation forest algorithm I have downloaded the sklearn branch containing it. ( https://github.com/ngoix/scikit-learn/tree/iforest) I have extracted the file in a local folder and I have built it with the command: python3 setup.py build_ext --inplace Everything see

[Scikit-learn-general] Get Other Classification Metrics For GridSearch

In performing a grid search, I know we can get overall accuracy, but I'm also interested in the minority F score. Is there a way to get that for each parameter setting combination? Thanks, Adam -- *Adam Goodkind * adamgoodkind.com @adamgreatkind

[Scikit-learn-general] using forkserver through GridSearchCV and friends

Hi, Is there anyway to specify the backend used by joblib? It's not obvious to me and this doesn't seem to work. from multiprocessing import set_start_method set_start_method("forkserver") I get a ton of "RuntimeError: context has already been set" exceptions. On Python 3.4.2, sklearn 0

Re: [Scikit-learn-general] Help with isolation forest algorithm

I did not solve yet but I think that the problem is related to the way I count the length of each path. I do it dynamically during the construction of the forest while they do it at the end. This seems to lead to slightly different results. Thanks anyway :-) On Fri, May 8, 2015 at 3:26 AM, Nico

Re: [Scikit-learn-general] deep learning NN based on UFLDL

Hi. There was just a thread about neural nets yesterday: https://sourceforge.net/p/scikit-learn/mailman/scikit-learn-general/thread/554BA4ED.9010205%40gmail.com/#msg34093050 There is lasagne https://github.com/Lasagne/Lasagne and keras https://github.com/fchollet/keras and nolearn https://github