"Radford Neal" <[EMAIL PROTECTED]> wrote:
> Yes, but are the distributions of symptoms given the diseases
> adequately described by Gaussian distributions?  If not, then the
> number of Gaussian components needed to described the overall
> distribution of symptoms will not equal the number of diseases.

A very valid concern -- the problem is in using only Gaussian
distributions, and would be remedied by using other types in
modelling.

An axis-aligned Gaussian with a diagonal covariance matrix is nothing
else than a mean with a central tendency and can be described as
follows:

age = 40 +- 10
temperature = 37 +- 2
glucose = 130 +- 20
urine_test = positive (p=0.8) (binomial treated as Gaussian)

A state of health can be nicely described this way, because health is
about maintaining homeostasis. People use these descriptions very
often and without realizing that they correspond to Gaussians.
However, in practice, there are situations where a distinguishing
characteristic is not a central tendency but a breakdown in it. For
example

temperature +- 10 > 40

For describing states like that, Gaussians are no longer particularly
suitable one would need a different kind of a model, and I haven't
seen good alternatives, other than the usual practice of ditching
interval scales and adopting ordinal/nominal ones. Perhaps someone
reading this post has?

-- 
mag. Aleks Jakulin
http://ai.fri.uni-lj.si/aleks/
Artificial Intelligence Laboratory,
Faculty of Computer and Information Science, University of Ljubljana.





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