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Does This Spark an Idea? Principal Component Analysis (PCA) of Yesterday and Today

(Last Updated On: April 30, 2012)

Does This Spark an Idea? Principal Component Analysis (PCA) of Yesterday and Today

http://www.geniq.net/res/Principal-Component-Analysis-Yesterday-and-Today.html

Principal Component Analysis of Yesterday and Today geniq.net

 

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we’ve just covered PCA in my Data Mining class, and so I’d be interested in reading more of your article. Thanks!

 

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The article is actually a chapter in my new book
http://www.geniq.net/statistical-machine-data-mining-Bruce-Ratner-book.html .
However, if you rather not buy, I will be glad to chat with you.

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Interesting. I am definitely interested in highly correlated eigengenes as a way to find expression networks.

 

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PCA has long been a key part of my toolbox for dealing with high-dimensional data. At the start, it’s a good way to check whether samples cluster by treatment in a PCA biplot. Then I look at which variables have the highest loading on each principal component, which often gives an initial idea what the main biological trends in the response of the samples might be. At later stages I may filter variables by ANOVA then do PCA just using a subset of variables.

 

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

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