Authors: R.P. Datta; Sanjib Saha
Addresses: Department of Information Technology, Indian Institute of Foreign Trade, Kolkata Campus, Premise No. 1583, Madurdaha, Kolkata-700107, West Bengal, India ' Department of Computer Science and Engineering, Dr. B.C. Roy Engineering College, Jemua Road, Fuljhore, Durgapur, West Bengal, 713206, India
Abstract: In the process of analysing and interpreting medical data, various classification techniques have been widely applied with a lot of success. A number of classification algorithms are available for this purpose and many researchers face the problem of choosing the best method for a particular dataset. In this paper, we apply five well-known, rule-based classification techniques on different medical datasets and compare their relative merits and demerits. Subsequently, we interpret their applicability in classifying patients into groups.
Keywords: data mining; knowledge discovery; rule-based classification; medical databases; medical data; patients; patient groups; patient classification; machine learning; association rules mining; decision tables.
International Journal of Business Intelligence and Systems Engineering, 2016 Vol.1 No.1, pp.32 - 48
Received: 22 Nov 2014
Accepted: 01 Jul 2015
Published online: 16 Jan 2017 *