Dimensionality reduction: the scikit is available !

My manifold learning code was for some time a Technology Preview in the scikit learn. Now I can say that it is available (BSD license) and there should not be any obvious bug left..

I’ve written a small tutorial. It is not an usual tutorial (there is a user tutorial and then what developers should know to enhance it), and some results of the techniques are exposed in my blog. It provides the basic commands to start using the scikit yourself (reducing some data, projecting new points, …) as well as the expoed interface to enhance the scikit.

If you have any question, feel free to ask me, I will add the answers to the tutorial page so that everyone can benefit from it.

Be free to contribute new techniques and additional tools as well, I cannot write them all ! For instance, the scikit lacks some robust neighbors selection to avoid short-cuts in the manifold…

Tutorial and the learn scikit mainpage.

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3 thoughts on “Dimensionality reduction: the scikit is available !

  1. Great job Matt !

    I’m gonna give a whirl to the scikit probably tomorrow. I’ll keep you informed and probably ask you some questions.

  2. It’s is the learn scikit. So you have to download the whole package (dedicated to machine learn) inside the learn folder.

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