Extraction of classification rules from socio-demographics and biochemistry datasets of schizophrenia patients using multi-objective genetic algorithms

This paper presents a method for extracting automatically classification rules via multi-objective genetic algorithms. The paper also proposes a novel objective measure to quantify the similarity of the rules. The other objectives of the rules are average support value and accuracy. We experimentally evaluate our approach on socio-demographics and biochemistry datasets of schizophrenia patients and demonstrate that our algorithm encourages us to improve and apply this strategy in many real-world applications.