A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction

A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction

June 11, 2008 Matt 2 Comments Python, Manifold learning

At last, my article on manifold learning has been published and is accessible with doi.org (it was not the case last week, that’s why I waited before publishing this post).
The journal is free, so you won’t have to pay to read it : Access to the EURASIP JASP article

I will publish additional figures here in a short time. The scikit is almost completed as well, I’m finishing the online tutorial for those who are interested in using it and/or enhancing it.

2 thoughts on “`A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction`”

Thomas Girault says:

June 18, 2008 at 3:17 PM

Hello Matt,

I am a Phd student (Rennes, France) in the domain of natural language processing.
I would be very interested to try your manifold learning algorithms with data extracted from texts.

Is your code available somewhere ?

Thanks.

Thomas Girault

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Matt says:

June 18, 2008 at 9:20 PM

Hi Thomas !

You can get the code from the scikit learn, available on http://scipy.org/scipy/scikits. I’ve included there a small tutorial, but I’ll make an official announcement at the end of next week (I’m on vacation for the time being).

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2 thoughts on “A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction”

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2 thoughts on “`A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction`”