Frank,

>>Also my measure would include learnability as a factor.  It would not
>>be driven purely by architectural demands and niceties.
>
>'Learnability'.  Care to quantify that?  :-)

This is where the classification work gets interesting.
Quoting from Estes, page 40:

"It has been demonstrated that some behavioral measures,
eg the order in which individuals list exemplars of categories,
are correlated with typicality ratings, one might wonder
whether relative typicalities computed from similarity-to-category
values could be interpreted as predicted probabilities of
categorization responses."

I may have misunderstood some parts of this work.  But it
looks as if various studies have confirmed the predictive power
of this proposal.  So learnability can be computed using
similarity-to-category.  The number that pops out the end
is the probability that a subject will categorize an instance as
belonging to the given category.

There are various complications, such as working out values
for similarity and what is called psychological distance.

In some cases no similarity values need be known.  For
instance Estes gives the example of two different ways
of classifying black/white triangles/squares.  In one case
the response probability is 1/(1+s) and in the other
(1 + s.s)/((1+s)(1+s)).  With s varying between 0 and 1.
For all values of s the first response probability is always
greater than or equal to the second.  Thus, the first classification
has the higher probability of subjects correctly classifying
instances that belong to it.


derek

--
Derek M Jones                                           tel: +44 (0) 1252 520 667
Knowledge Software Ltd                            mailto:[EMAIL PROTECTED]
Applications Standards Conformance Testing   http://www.knosof.co.uk



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