Author: Ingo Althofer
Date: 12:06:34 12/30/05
Go up one level in this thread
On December 30, 2005 at 13:47:15, Roger D Davis wrote:
>On December 30, 2005 at 13:02:43, Ingo Althofer wrote:
> in case of linear evaluation functions with lots
>>of terms there is always a small subset of the terms
>>such that this set with the right parameters is
>>almost as good as the full evaluation function.
>
>The whole multivariate approach to the social sciences, of which multiple linear
>regression is an example, is based on the same assumption.
^^^^^^^^^^^^^^^^
My result mentioned above is not an assumption, but
a proof (with arguments from linear algebra and
probability theory).
But, of course, it is not an accidence that the
principal component analysis works so well in
many (also social) sciences.
>Parsimony rules.
Or, formulated more positively:
"Occams razor is the best we have!"
Ingo.
This page took 0 seconds to execute
Last modified: Thu, 15 Apr 21 08:11:13 -0700
Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.