Optimal Decision Tree Fuzzy Rule Based Classifier (ODT-FRC) For Heart Disease Prediction Using Improved Cuckoo Search Algorithm

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.