Re: [Scikit-learn-general] LogisticRegression regularizes intercept

that if you use a L2 regularization instead, you can also try the 3 other solvers ("newton-cg", "lbfgs" and "sag"), which do not regularize the intercept and that also handle multinomial loss. Best, Tom 2016-03-15 10:03 GMT+01:00 David Ojeda : > Hello scikit-learners, > &g

Re: [Scikit-learn-general] performance/scalability of NMF

<https://gist.github.com/TomDLT/c1d560a510a41dd80ab6>: Best, Tom 2016-03-11 12:26 GMT+01:00 Roberto Pagliari : > Are there results about performance and scalability of scikit-learn > implementation of NMF? > > According to this thread on SO > > > http://stackoverflow.com/quest

Re: [Scikit-learn-general] Dropping Python 2.6 compatibility

For what it’s worth, pandas is dropping 3.3 in our next release (0.18 maybe end of this month). We’re possibly dropping 2.6 as well, but it might get one more release. -Tom > On Jan 4, 2016, at 7:28 AM, Gael Varoquaux > wrote: > > Happy new year everybody, > > As a new

Re: [Scikit-learn-general] Finding conditional Gaussian Mixture Model using scikit-learn.mixture.GMM

On 02/02/2015, Alexander Fabisch wrote: > I implemented that > in another library (https://github.com/AlexanderFabisch/gmr, example: > https://github.com/AlexanderFabisch/gmr/blob/master/examples/plot_estimate_gmm.py). I tried out your code, but it crashed when attempting to generate samples from

Re: [Scikit-learn-general] Finding conditional Gaussian Mixture Model using scikit-learn.mixture.GMM

Wow, fast responses, thanks! On 02/02/2015, Andy wrote: > I don't see how this would fit into the standard sklearn interface... Just what Alexander said. I don't know sklearn well enough to know what the standard pattern for interfacing might be, or why this presents a problem. I was expecting t

[Scikit-learn-general] Finding conditional Gaussian Mixture Model using scikit-learn.mixture.GMM

asy way of doing this (in which case, could it be added as an example in the documentation?) or might it get added to sklearn? Thanks in advance, Tom -- Dive into the World of Parallel Programming. The Go Parallel Websit

Re: [Scikit-learn-general] Exclusivity of scikit-learn

> > On Dec 4, 2014, at 2:00 AM, Sturla Molden wrote: > > Tom Fawcett wrote: > >> Wow, I had not seen this FAQ. "As a rule we only add well-established >> algorithms. A rule of thumb is at least 3 years since publications, 1000+ >> cites and wide use an

Re: [Scikit-learn-general] Exclusivity of scikit-learn

the immense work that’s gone into the project, and if that’s the way it’s run, so be it. Regards, -Tom -- Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server from Actuate! Instantly Supercharge Your Bus

[Scikit-learn-general] Exclusivity of scikit-learn

e decision tree induction method. Anyone know of another python framework that’s a little more welcoming? -Tom -- Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server from Actuate! Instantly Sup

[Scikit-learn-general] linear_model.SGDClassifier(): ValueError: ndarray is not C-contiguous when calling partial_fit()

says: Flags of coef_ array: C_CONTIGUOUS : False F_CONTIGUOUS : True OWNDATA : True WRITEABLE : True ALIGNED : True UPDATEIFCOPY : False I am sure I am doing something wrong, but really, I don't see what... Any help appreciated! Cheers, Tom --

Re: [Scikit-learn-general] Release 0.14: tagged and pushed!

intentional? I don’t see any discussion of it on Scikit-learn-general, but maybe it was discussed elsewhere. If Reuters-21578 is now being distributed with sklearn, maybe you should alter the README.txt file in that directory to reflect that it’s OK with D.Lewis, Reuters, etc. Regards, -Tom Gael

Re: [Scikit-learn-general] Text processing using nltk, sklearn and pandas

of > large-scale feature extraction jobs.) I’m curious – why? Thanks, -Tom -- See everything from the browser to the database with AppDynamics Get end-to-end visibility with application monitoring from AppDynamics Isolat

[Scikit-learn-general] Text processing using nltk, sklearn and pandas

interface package, or best practices documentation, for using them together to do large-scale text processing? I can write my own glue code if I have to, but I’d rather not reinvent the wheel. Thanks, -Tom -- This SF.net

Re: [Scikit-learn-general] Clustering of Text Documents

earn) is at the junction of several fields, and there are numerous terms (bias, convex, confidence, support, frequency, decision tree) with conflicting meanings. I suggest where there is a chance for confusion the documentation should make meanings explicit.

[Scikit-learn-general] Small bug/inconsistency in sklearn.feature_extraction.text.CountVectorizer

demonstrates the problem. It took a while to figure out why (in a larger program) I was getting this error. I am using sklearn.cross_validation.StratifiedKFold which returns an index array for each fold, and the program broke when I started using CountVectorizer. Regards, -Tom

[Scikit-learn-general] Relational learning with scikit-learn

any pointers, -Tom -- Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_d2d_mar

Re: [Scikit-learn-general] Easy way to handle .arff files in sklearn?

#x27;yes'] ['blue' '27.2' '2' 'yes'] ['blue' '18.2' '3' ’no’]] I’ve been using Lars Buitinck’s arff reader (thanks Lars!) which does numerical encodings, which are necessary for most of scikits-learn. Regards, -Tom On Mar

[Scikit-learn-general] Easy way to handle .arff files in sklearn?

directory and I did some google searches but nothing obvious is uncovered. Thanks, -Tom -- Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today

[Scikit-learn-general] Problem in text feature extraction (sklearn.feature_extraction.text)

that the default is: token_pattern=u'(?u)\b\w\w+\b’ The quoted regexp needs an r in front of it, without which the \w is interpolated in the string. Regards, -Tom -- Everyone hates slow websites. So do we