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 doesnt) 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 couldnt find for genetic.
All help/comments welcome.
Thanks
Stephen
--
27/09/2005
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