[R] assessing performance of a classfication method

[Evgenia Dimitriadou]

if i understood right you want to match the class labels to the clustering
labels. try matchClasses in library(e1071).
best,
-e
On 19 Mar 2002, Allan Strand wrote:

> 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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*                          Evgenia Dimitriadou                         *
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* Institut für Statistik      *               Tel: (+43 1) 58801 10773 *
* Technische Universität Wien *               Fax: (+43 1) 58801 10798 *
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