In this digital world, the number of cardiovascular disease cases is growing exponentially every day like never before in the globe. The timely prognosis of heart disease with careful treatment and implementation of a healthy lifestyle with further research can help to prevent many cardiovascular diseases at the earliest. When it comes to investigating unclear data from particular clinical information collections, clinical data mining is very efficient. This research work aims to provide recent methods of knowledge discovery in databases that are in use for the classification of cardiovascular disease nowadays. Various classification techniques are compared and analyzed for cardiovascular dataset by applying the feature relevance analysis and the Precision Scrutiny to come up with the best classification rule. Also, the aim of the study is to filter the data in a way that healthy people and people with cardiovascular disease are classified correctly. In this work, it is applied that the k-Nearest Neighbor (k-NN), JRip, Random Forest, and AdaBoostM1 methods to find and analyses the heart disease from the chosen data set. The data set is taken from the web sources. The best method for the prediction of heart disease is suggested finally in this analysis.

Keywords: Classification techniques, JRip Algorithm , AdaBoostM1 Algorithm, Random Forest Algorithm, k-Nearest Neighbor (k-NN) Algorithm.

Dr. T. Velmurugan is working as an Associate Professor in the PG and Research Department of Computer Science and Applications, Dwaraka Doss Goverdhan Doss Vaishnav College, Chennai-600106, India. Also, he is the Advisor and Head, Department of Computer Applications (BCA). He holds a Ph.D. degree in Computer Science from the University of Madras. He has 28 years of teaching experience. He guided more than 300 M.Phil., Research Scholars. Also, he guided 17 Ph.D. scholars and currently guiding 6 Ph.D. scholars. He has published more than 110 articles in SCOPUS and SCI indexed journals. He elected and served as a Senate Member from Academic Council, University of Madras. He has a lot of administrative experiences. He served as advisory board member to many academic institutions in and around Tamil Nadu, India He was an invited speaker and keynote speaker for many international conferences around the world. He served as a nominated Senate Member in the Middle East University, Dubai, UAE for a period of three years. He is a member in Board of studies for many autonomous institutions and Universities. Also, he organized international Conferences and workshops. In addition, he was a resource person for various national workshops entitled "Scientific Research Article Writing and Journal Publications" and many of the recent topics in Computer Science. He is an Editorial Board Member of 6 International Journals. He also a reviewer in many peer reviewed journals like Elsevier, Springer, IEEE and IOSPress Journals etc. He is the Chair person for the Government of Tamil Nadu State for XII standard book titled as “Electronics and Hardwares”. Further, he is a visiting faculty for M.Phil. Course for various universities throughout India. His H index is 18 and i10 index is 27. His area of specialization includes Data Mining, Artificial Intelligence, Machine Learning, Network Security, Big Data Analytics, Data Science and etc.