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 -- 27/09/2005 [[alternative HTML version deleted]]