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Difference between revisions of "Tips:Implement Regularized Discriminant Analysis in SAS"

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<div style="float:right">Submitted By [[User:http&#58;//|Liang Xie]]</div>
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Revision as of 22:00, 17 January 2012

Friedman proposed Regularized Discriminant Analysis (RDA) to overcome multicollinearity and other causes that make LDA/QDA ill-conditioned. The core idea is to regularize illy-conditioned within class covariance matrix with the pooled covariance matrix for QDA or to regularize illy-conditioned pooled covariance matrix with a diagonal matrix for LDA. For details about this algorithm, check the book: Elements of Statistical Learning, Chapter 4, section 3.1.

To implement RDA, we output sufficient statistics using OUTSTAT= in PROC DISCRIM and make appropriete changes to relavant statistics, then use the scoring functionality fo PROC DISCRIM to re-score the data with regularized covariance matrix. See link below for sample code on Regularized LDA.

....see also

Submitted By Liang Xie