Hi 
 
I have a largish dataset (26 columns 35000 rows) which I have been
subjecting to logistic regression and support vector machine analysis.
I have noticed that R easily copes with using the data in either
technique.  Now I have to try and see what the best modeling technique
to use is. 
 
I only have limited time (who doesn’t) so I thought it would be best to
try the data with any other techniques on R that can handle that data
set and then use predict()  and so on.  I have identified the following
techniques (you may know of more) and think the packages indicated will
support them:
 
Neural networks             ->         AMORE
Genetic/evolutionary       ->         ?
Bayes                           ->         deal
Decision trees               ->         knnTree
Gaussian processes      ->         predict
 
Are these the right packages where I can go model = etc,
predict(model,etc using my dataset?
 
Have I missed some techniques?
 
Does anyone know the package I couldn’t find for genetic.
 
All help/comments welcome.
 
Thanks
 
Stephen
 
 

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27/09/2005
 

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