[R] Boosting, bagging and bumping. Questions about R tools and predictions.

[Ko-Kang Kevin Wang]

Hi,

If you want to learn the theory of boosting and bagging, and other 
classification techniques, then you will want to refer to Hastie, 
Tibshirani and Friedman's "The Element of Statistical Learning: Data 
Mining, Inference, and Prediction" by Springer.  It is the best book I 
have seen in these areas.

To apply them (or some of the techniques) in R, the book you want to look 
at is Venables and Ripley's MASS 4 (Modern Applied Statistics with S).

On Tue, 22 Jul 2003 monkeychump at hushmail.com wrote:

> Date: Tue, 22 Jul 2003 17:09:47 -0700
> From: monkeychump at hushmail.com
> To: r-help at stat.math.ethz.ch
> Subject: [R] Boosting,
>      bagging and bumping. Questions about R tools and predictions.
> 
> 
> I'm interested in further understanding the differences in using many
> classification trees to improve classification rates. I'm also interested
> in finding out what I can do in R and which methods will allow prediction.
> Can anybody point me to a citation or discussion?

-- 
Cheers,

Kevin

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--
Ko-Kang Kevin Wang
Master of Science (MSc) Student
SLC Tutor and Lab Demonstrator
Department of Statistics
University of Auckland
New Zealand
Homepage: http://www.stat.auckland.ac.nz/~kwan022
Ph: 373-7599
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