Handling Over-fitting and Class-imbalance Jointly in Pittsburgh LCS.

      Аннотация: Generalization ability of a classi?er is an important issue for any classification task. Two prominent problems affecting the generalization ability are over-?tting and class-imbalance. This book presents a new evolutionary system, i.e., EDARIC, for rule induction and classi?cation. The evolutionary approach used in our new system is based on a destructive method that starts with large-sized rules and gradually decreases the sizes as evolution progresses. The experimental results show that our proposed evolutionary system obtains better generalization performance compared to the existing algorithms.

Ключевые слова: class imbalance, Evolutionary Algorithms, learning classifier systems, Machine Learning, Over-fitting