I'm using Weka to perform classification, clustering, and some regression on a few large data sets. I'm currently trying out all the classifiers (decision tree, SVM, naive bayes, etc.).
Is there an automated way (in Weka or other machine learning toolkit) to sweep through all the available classifier algorithms to find the one that produces the best cross-validated accuracy or other metric? I'm not talking about boosting; rather, I'm looking to just choose the best classifier using a given data set.
I'd like to find the best clustering algorithm, too, for my other clustering problem; perhaps finding the lowest sum-of-squared-error?