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Principal Component Analysis

Posted by Ib / Vce(sat) on November 6, 2007

I was just looking for some information on ISOMAP . I had then hit by the terms PCA and MDA a multiple times that i decided to give it a good glance . Though i am looking for somehting on machine learning , currently i am into a work with one of my professors who wants to implement AI into some kind of pattern recognition in flow cytometry.

So I have started looking at these topics and i am really amazed at the statistics involved in pattern recognition. So i just give a link here to a tutorial that provides a very clear explanation about PCA method of reduction of high dimentional data.

THE LINK
http://csnet.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf

Hope it amuses some of you too

-Madan

One Response to “Principal Component Analysis”

  1. In the hopes that this might be of interest to you or anyone reading this, MDA (“multiple discriminant analysis”) also goes by the name “canonical discriminants”, and is related to, but distinct from “linear discriminant analysis”. It is a terminology jungle!

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