PREDICTION IN DATA MINING COMPARATIVE STUDY OF HEART DISEASE
Journal Title: Elysium Journal of Engineering Research and Management - Year 2016, Vol 3, Issue 4
Abstract
Data mining is the process of finding useful and relevant information from the databases. There are several types of data mining techniques are available. Association Rule, Classification, Neural Networks, Clustering are some of the most important data mining techniques. Data mining process may take important role in Health care Industries. Most commonly the data mining process is used in health care industries for the process of prediction of diseases. This paper analysis the Heart Disease prediction approaches using classification technique. Here we are using three different kinds Decision tree, Rule Approaches, Logical statements (ILP), Bayesian Classifiers, Support Vector Machines, k-nearest neighbor classifiers, WEKA, Logistic regression, J48, Genetic Classifiers. We have taken the data set from the UCI repository which is used here.
Authors and Affiliations
Viswanathan K, Mayilvahanan K, Christy Pushpaleela R
Keywords
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