I have a small data set consisting of 385 entries and around 200 attributes. Because I want to apply attribute selection and because of the limited size of my data set, I got the advice to use the random forest classifier, because it got attribute selection build in and does not require an extra training set to determine the attributes to be used.
My question is if it is also possible in WEKA to visualize the final tree of the random forest classifier, so that I can see which attributes are eventually selected? If I set the debug option, I only see the intermediate trees.
Can I for example also determine the attributes that are eventually selected using the random forest classifier in the attribute selection tab of the WEKA explorer, or will this result in other attributes being selected?