Scikit-learn 0.13: Nystroem method, hashing trick, faster random forests

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46 pointsogrisel3 comments

The scikit-learn developers are also interested in knowing more about organizations using the library for building innovative products or solving data related problems.

If you are interested in writing a short paragraph about how your organization is using scikit-learn please feel free to contact me or another developer of the project. The goal would be to have this published in a future testimonials page on the project website.

This is awesome.

Not yet an organization here, but I've used scikit-learn for my internship project and thesis.

Something I implemented during that work (barely working) was the EM algorithm. I was wondering if EM is of any interest of the library.

Expectation Maximization is a very generic inference scheme that has many declination depending on the structure of the models it is applied to. For instance there we already have Gaussian Mixture Models that can be fitted using EM in sklearn. There is also an implementation of k-means which can also be interpreted as an EM algorithm.

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