[scikit-learn] New to scikit

Hi everyone, I have a prior experience in python, and have started learning machine learning recently. I wanted to contribute to scikit, can anyone suggest a relatively easy codebase to explore. Thanks in advance! ___

Re: [scikit-learn] New to scikit

Great! Welcome to the community. I would suggest you to check out the issues page on the github repo, raise hand to the issues you feel like you can give a go to, check out the issues that are tagged as require contributor. Issues are a good way to start, they will direct you about the areas of the

Re: [scikit-learn] New to scikit

Yeah, I found an easy bug. Looking for some help in writing deprecation cycles for a bug. On Wed, Dec 7, 2016 at 8:05 PM, Siddharth Gupta wrote: > Great! Welcome to the community. I would suggest you to check out the > issues page on the github repo, raise hand to the issues you feel like you >

[scikit-learn] Latent Dirichlet Allocation transformation of data with pre-determined topic_word distribution

Hello, I am running Latent Dirichlet Allocation 100 times on bootstrapped versions of a dataset, gathering up the topic_word matrix from each run (components_), and merging it into a final cleaner topic_word matrix. Because I am bootstrapping documents, not every document is in every run and so it

Re: [scikit-learn] New to scikit

http://scikit-learn.org/dev/developers/contributing.html#deprecation On 12/07/2016 09:42 AM, Chinmay Talegaonkar wrote: Yeah, I found an easy bug. Looking for some help in writing deprecation cycles for a bug. On Wed, Dec 7, 2016 at 8:05 PM, Siddharth Gupta mailto:siddharthgupta...@gmail.com>

Re: [scikit-learn] Nested Leave One Subject Out (LOSO) cross validation with scikit

On 12/07/2016 07:41 AM, Ludovico Coletta wrote: Dear scikit experts, I did as you suggested, but it is not exactly what I would like to do ( I also read this: http://stackoverflow.com/questions/40400351/nested-cross-validation-with-stratifiedshufflesplit-in-sklearn) Perhaps I should ask

[scikit-learn] return type of StandardScaler

StandardScaler returns numpy array even if the object passed is a pandas dataframe, shouldn't it return a dataframe? ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] return type of StandardScaler

you can use pandas.get_dummies() . It will perform one hot encoding on categorical columns, and produce a dataframe as the result. From there you can use pandas.concat([existing_df, new_df],axis=0) to add the new column

Re: [scikit-learn] return type of StandardScaler

On 12/07/2016 11:44 AM, Nilay Shrivastava wrote: StandardScaler returns numpy array even if the object passed is a pandas dataframe, shouldn't it return a dataframe? See https://github.com/scikit-learn/scikit-learn/issues/5523 sklearn-pandas might be of help for now. ___

[scikit-learn] Nested Leave One Subject Out (LOSO) cross validation with scikit

al and Events Coordinator, Mood Indigo > .. > > > +91-8879178724 > chinmay0...@gmail.com <mailto:bajajkshiti...@gmail.com> > www.moodi.org<http://www.moodi.org> <http://www.moodi.org/> > > > > > > ___ > scik

Re: [scikit-learn] Nested Leave One Subject Out (LOSO) cross validation with scikit

g> <http://www.moodi.org/> > > > > > > ___ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn -- next part -- An HTML attachment was s

Re: [scikit-learn] Nested Leave One Subject Out (LOSO) cross validation with scikit

istinfo/scikit-learn > > <https://mail.python.org/mailman/listinfo/scikit-learn> > > > > > > > > > > -- > > -- > > *Chinmay Talegaonkar* > > Cultural and Events Coordinator, Mood Indigo > > ..

[scikit-learn] NuSVC and ValueError: specified nu is infeasible

Greetings, I want to use the Nu-Support Vector Classifier with the following input data: X= [ array([ 3.90387012, 1.60732281, -0.33315799, 4.02770896, 1.82337731, -0.74007214, 6.75989219, 3.68538903, .. 0., 11.64276776, 0.

[scikit-learn] no positive predictions by neural_network.MLPClassifier

I tried the sklearn.neural_network.MLPClassifier with the default parameters using the input data I quoted in my previous post about Nu-Support Vector Classifier. The predictions are great but the problem is that sometimes when I rerun the MLPClassifier it predicts no positive observations (class 1

Re: [scikit-learn] no positive predictions by neural_network.MLPClassifier

Hi, Thomas, we had a related thread on the email list some time ago, let me post it for reference further below. Regarding your question, I think you may want make sure that you standardized the features (which makes the learning generally it less sensitive to learning rate and random weight ini

Re: [scikit-learn] Github project management tools

And yet GitHub just rolled out a new "reviewers" field for assigning these things... On 7 December 2016 at 03:26, Raghav R V wrote: > +1 for self assigning PRs by reviewers... > > On Tue, Dec 6, 2016 at 4:19 PM, Andy wrote: > >> Thanks for your thoughts. >> I'm working in a similar mode, though

Re: [scikit-learn] NuSVC and ValueError: specified nu is infeasible

Hi Thomas, the doc says, that nu gives an upper bound on the fraction of training errors and a lower bound of the fractions of support vectors. http://scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVC.html Therefore, it acts as a hard bound on the allowed misclassification on your dat