title: SM-RuleMiner: Spider monkey based rule miner using novel fitness function for diabetes classification.
abstract: Diabetes is a major health challenge around the world. Existing rule-based classification systems have been widely used for diabetes diagnosis, even though they must overcome the challenge of producing a comprehensive optimal ruleset while balancing accuracy, sensitivity and specificity values. To resolve this drawback, in this paper, a Spider Monkey Optimization-based rule miner (SM-RuleMiner) has been proposed for diabetes classification. A novel fitness function has also been incorporated into SM-RuleMiner to generate a comprehensive optimal ruleset while balancing accuracy, sensitivity and specificity. The proposed rule-miner is compared against three rule-based algorithms, namely ID3, C4.5 and CART, along with several meta-heuristic-based rule mining algorithms, on the Pima Indians Diabetes dataset using 10-fold cross validation. It has been observed that the proposed rule miner outperforms several well-known algorithms in terms of average classification accuracy and average sensitivity. Moreover, the proposed rule miner outperformed the other algorithms in terms of mean rule length and mean ruleset size.
authors.affiliation: Department of Computer Science and Engineering, National Institute of Technology Goa, Ponda, Goa 403401, India. Electronic address: rmlswamygoud@nitgoa.ac.in.
authors.forename: Ramalingaswamy
authors.initials: R
authors.lastname: Cheruku
authors.affiliation: Department of Computer Science and Engineering, National Institute of Technology Goa, Ponda, Goa 403401, India. Electronic address: dr.reddy@nitgoa.ac.in.
authors.forename: Damodar Reddy
authors.initials: DR
authors.lastname: Edla
authors.affiliation: Department of Computer Science and Engineering, National Institute of Technology Goa, Ponda, Goa 403401, India. Electronic address: venkatanaresh@nitgoa.ac.in.
authors.forename: Venkatanareshbabu
authors.initials: V
authors.lastname: Kuppili
mesh_terms: D000465:Algorithms; D000818:Animals; D053819:Atelinae; D032701:Biomimetics / Q000379:methods; D057225:Data Mining / Q000379:methods*; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D003920:Diabetes Mellitus / Q000145:classification / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D057286:Electronic Health Records / Q000458:organization & administration*; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Classification rules; Diabetes diagnosis; Optimal ruleset; Rule-based algorithms; Spider monkey optimization