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From: saswss@hotellng.unx.sas.com (Warren Sarle)
Subject: Re: NN Vs Stats......
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Date: Thu, 26 Jan 1995 00:10:36 GMT
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In article <3g61v0$5p2@netnews.upenn.edu>, korovi25@equity.wharton.upenn.edu (ANDREI KOROVIKOV) writes:
|>      A lot of people are arguing semantics here. Statistics is what
|> you define it to be, no more and no less.

I prefer to think of statistics as what statisticians define it to be.

|>      I personally think of two "statistics" -- one is "statistics in
|> general", which, for me, is just the science/art/craft of making sense
|> out of quantitative data (clearly, this includes NNs);

That's "data analysis", which obviously includes NNs that are used for
data analysis and does not include NNs used for other purposes.

|> and the other one
|> is "classical statistics", which thinks of sampling populations, white
|> noise, linear approaches, etc. This classical statistics does not include
|> NNs.

"Classical statistics" surely covers feedforward nets trained by
least squares or cross entropy, functional link nets, higher order
nets, probabilistic neural nets, general regression neural nets, etc.
I have posted references several times.

-- 

Warren S. Sarle       SAS Institute Inc.   The opinions expressed here
saswss@unx.sas.com    SAS Campus Drive     are mine and not necessarily
(919) 677-8000        Cary, NC 27513, USA  those of SAS Institute.
