作者: M. A. Jabbar , B. L. Deekshatulu , Priti Chandra
DOI: 10.1007/978-3-642-32063-7_4
关键词: Set (psychology) 、 Population 、 Association rule learning 、 Disease 、 Cause of death 、 Machine learning 、 Data mining 、 Knowledge extraction 、 Decision support system 、 Heart disease 、 Artificial intelligence 、 Computer science
摘要: Associate classification is a scientific study that being used by knowledge discovery and decision support system which integrates association rule methods to model for prediction. An important advantage of these systems that, using mining they are able examine several features at time. Associative classifiers especially fit applications where the may assist domain experts in their decisions. Cardiovascular deceases number one cause death globally. estimated 17.3 million people died from CVD 2008, representing 30% all global deaths. India risk more deaths due CHD. disease becoming an increasingly Andhra Pradesh. Hence proposed predicting heart patient. In this paper we propose new algorithm Pradesh population. Experiments show accuracy resulting set better when compared existing systems. This approach expected help physicians make accurate