Title: Optimal decision tree fuzzy rule-based classifier for heart disease prediction using improved cuckoo search algorithm

Authors: Subhashini Narayan; Jagadeesh Gobal

Addresses: School of Information Technology and Engineering, VIT University, Vellore, India ' School of Information Technology and Engineering, VIT University, Vellore, India

Abstract: Heart disease is a major cause for anomaly in developed countries and one of the basic diseases in developing countries. Then there is a necessary to insert an alternative expressively caring network for predicting heart disease of a patient. The clinical alternative expressively caring networks contain three method of preprocessing such as preprocessing, generate decision rule and rule weighting, classification. Initially, the Cleveland data, Hungarian data and Switzerland data are loud in the reliable information from the database in preprocessing. On this process, underline quantity reduction method will be associated to reduce the components space exploiting orthogonal neighbourhood safeguarding projection (OLPP) computation. While, the combinations of cuckoo search algorithm, fuzzy and decision tree classifier can create a hybrid classifier. Here, fuzzy and decision tree algorithm will be sufficiently combined with cuckoo search (CS) algorithm and which will guide for accurate grouping.

Keywords: preprocessing; cuckoo search; fuzzy; decision tree; classification.

DOI: 10.1504/IJBIDM.2019.102810

International Journal of Business Intelligence and Data Mining, 2019 Vol.15 No.4, pp.408 - 429

Received: 24 Aug 2016
Accepted: 13 Sep 2016

Published online: 30 Aug 2019 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article