Re: [R] multi-class modeling

From: Prof Brian Ripley <ripley_at_stats.ox.ac.uk>
Date: Mon 11 Apr 2005 - 17:35:57 EST

All of this is addressed in the reference for multinom(): it is support software for a book.

(You are likely to get a more sympathetic response if you use a real name and a signature giving your true affiliation.)

On Sun, 10 Apr 2005, 'array chip' wrote:

> Just wonder if someone could comment on using linear
> discriminant analysis (LDA) vs. multinomial logistic
> regression in multi-class classification/prediction
> (nomial dependent variable, not ordinal)? What kind of
> difference in results can I expect from the 2 methods,
> which is better or more appropriate, or under what
> condiditon should I used one instead of the other? And
> is there other methods I can try?

> On another note, if I want to use logistic regression
> using multinom() in package nnet, how can I address
> the problem that each class of the dependent variable
> has an unequal prevalence? In lda(), I can do this by
> using prior argument, but there is no similar argument
> in multinom().

Depends what you think the `problem' is. In lda(), you usually do not adjust by the 'prior' argument. Is the problem that your training set is a biased sample? If so, see my PRNN book.

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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Received on Mon Apr 11 17:49:44 2005

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