weka J48 feature selection

Question

I am using Weka and applying J48 to build my classifier. I have 40 features with 2000 instances (700 class a and 1300 class b).

The J48 decision tree is just using 2 features out of 40! Is there anyway to allow J48 to use all features or is there any other algorithm that allows using all features?

Thanks in advance.

Answer 1

It is not necessary that all the 40 features are needed for the classification. Because some features might be redundant (e.g. correlated) or does not contain discriminatory information.

You can run feature selection before from the Select attributes tab in Weka Explorer and see which features are important.

Also you can test classifiers such as SVM (libSVM or SMO), Neural Network ( MultilayerPerceptron) and/or Random Forest as they tend to give the best classification results in general (problem dependent)

Answer 2

Maybe it is because J48 does not need more attributes.

You can check feature's correlation in Select attribute tab, and run the selector with Ranker as search method and Principal Components as evaluator. It will show you the relations between each feature and each class, and it will also tell you which are the features that best describe your classes.