On Sun, 22 Apr 2001 16:23:46 GMT, Robert Ehrlich <[EMAIL PROTECTED]>
wrote:
> Clustering has a lot of associated problems. The first is tha tof cluster
> validity--most algorithms define the existence of as many clusters as the user
> demands. A very important problem is homogeneity of variance. So a Z
> transformation is not a bad idea whether or not the variables are normal.
Unless you want the 0-1 variable to count as 10% as potent as the
variable scored 0-10. The classical default analysis does let you
WEIGHT the variables, by using arbitrary scaling. (Years ago, it was
typical, shoddy documentation of the standard default, that they
didn't warn the tyro. Has it improved? Has the default changed?)
> Quasi-normnality is about all you have to assume--the absence of intersample
> polymodality and the aproximation of the mean and the mode. However, to my
> knowledge, there is no satisfying "theory" associated withcluster analyis--only
> rules of thumb.
[ snip, original question ]
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
=================================================================
Instructions for joining and leaving this list and remarks about
the problem of INAPPROPRIATE MESSAGES are available at
http://jse.stat.ncsu.edu/
=================================================================
