[R] assessing performance of a classfication method

[David Meyer]

Allan Strand wrote:

Apart from matchClasses(), you might look at classAgreement(), also in
e1071.

g.
-d

> 
> Hi all,
> 
> I have developed a routine to classify observations based upon
> clustering.  In my current case there are 5 classes, so the data at
> the end of the classification look like this:
> 
> obs   class
> 1      2
> 2      2
> 3      1
> 4      4
> 5      4
> 6      3
> 7      5
> 8      5
> .      .
> .      .
> 
> I always know the numbers of classes a priori.  I wanted to see how
> well my approach is performing so I wrote a simulation to generate
> observations in a fairly realistic manner.  I then run the simulated
> observations through my scheme.  The "known" simulated data have the
> same form as the results of the classification, but the class
> identifiers may differ. In other words, a class of observations may be
> constructed correctly by my approach, but the "name" of the class may
> change.
> 
> I would like to compare the results of my scheme to the "known"
> simulated classes and assess its error rate.  AS I start, I would just
> like to know the number of observations that were mis-classified.  No
> doubt this is a brain-dead question to those who work in this field,
> but this is my first foray into such analyses.  Ultimately I was
> wondering of there is an R package that performs such analyses out of
> the box or if anyone who does these kind of analyses routinely has a
> code snippet I could use as an example.
> 
> Cheers,
> a.
> --
> Allan Strand,   Biology    http://linum.cofc.edu
> College of Charleston      Ph. (843) 953-8085
> Charleston, SC 29424       Fax (843) 953-5453
> 
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-- 
	Mag. David Meyer		Wiedner Hauptstrasse 8-10
Vienna University of Technology		A-1040 Vienna/AUSTRIA
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