Algorithm 1: Pseudo Code of Building Hybrid Model

Input: SA = selected attributes list, CD = collected data, RSES = rough set exploration system  Use attributes from SA;  Create 67% of data for training from CD;  Create the other 33% of data for testing from CD;  Define all the default parameters;  Apply RST classifier by RSES;  Apply DT, RF, MLP, and SVM classifiers, respectively;  Create tree-based rules sets by DT; Output: knowledge(tree)-based rules sets