I agree, but I'm not sure it the one that Cecilia talks about is a good fit.
MI based feature selection is still a field of pretty active research,
right? Is there a good review paper?
Or some set of standard algorithms?
On 02/23/2015 12:49 PM, Fred Mailhot wrote:
A good MI-based feature selector would be welcome, I think. Well, by
me, anyway.
On 23 February 2015 at 09:37, Andy <t3k...@gmail.com
<mailto:t3k...@gmail.com>> wrote:
Hi Cecilia.
An MI estimate currently seems a bit out of scope of sklearn.
What context would a user apply it in?
Sklearn currently contains more out-of-the-box methods, while an
MI estimator seems more like a building block.
Cheers,
Andy
On 02/23/2015 06:01 AM, cécilia wrote:
Hi,
May you tell me if you are interested by this measure (see my previous mail
below)? In which part of scikit-learn may I develop it : clustering, feature
selection?
Thanks,
Cécilia
Hi,
I have developped a script on mutual information estimation based on Renyi
entropy Cauchy-Schwartz divergence (and Parzen-Window function for continous
variables).This script allows to estimate MI between two disctete, continous
and mixed (discrete and continous) variables. I'll plan to first parallelize
the code and second to improve the code in order to estime MI between more than
two features.
If you are interested by this script, I can push the first version and
modify it according to your feedback.
Let me know.Greetings,Cécilia Damon
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