• SHUBHAM SHARMA
• DR. ANJANA PANDEY
• DR. MAHESH PAWAR

With the forthcoming pattern of online exchange in all parts measure of recently made data builds each year. Information mining characterization calculations can take after three extraordinary learning approaches: semi-supervised learning, supervised learning and unsupervised learning. In this paper we apply and dissect the generally utilized grouping calculations on therapeutic informational collection that predicts coronary illness that records to be the essential driver of death around the world. Decision trees are appeared to be not as sufficient for course illness expectation as affiliation rules. Tests demonstrate decision trees have a tendency to find couple of clear standards, most principles have genuinely low unflinching quality, and most attribute parts are not exactly the same as restoratively general parts, and most guidelines insinuate little plans of patients. Conversely, association rules for the most part incorporate less complex association rules, they function admirably with client binned properties, run dependability is higher and rules by and large allude to bigger arrangements of patients.

Algorithm, Classification, Diseases, Heart-Attack, J48

"Performance Evaluation of Classification Algorithm J48 on Heart attack and its diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 6, page no.253-258, June-2018, Available :http://www.jetir.org/papers/JETIR1806539.pdf

"Performance Evaluation of Classification Algorithm J48 on Heart attack and its diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 6, page no. pp253-258, June-2018, Available at : http://www.jetir.org/papers/JETIR1806539.pdf