The Attribute-Selected-Classifier is a combination of 2 steps: (1) dimensionality reduction through attribute selection, and (2) classification. The user gets to choose and customize from a variety of DR methods and classifiers in WEKA.

You can check the 2 steps separately:

- First, the DR step, by looking into the different attribute selection methods in WEKA. For some of the them, you can find reference and more information in the description of the method (see examples in the screenshots attached).

- Second, the classification step, by looking also for the information provided in WEKA. A good idea would be to check other published research, comparable to your needs, and see what classification methods are used.