What's the best way to approach a regression problem with a lot of features (over 300), many of which are categorical?
Try doing a Principal component analysis to get the reduced feature set and then apply regression techniques in loop to see which one predicts better. SVM may take sometime to execute so better exclude it. Random Forest should be a good fit in this case.