• Syed Rashid Anwar
• Gaurav Singh Janghel

Coronary illness is the primary justification behind death on the planet over the course of the past ten years. Right around one individual passes on from Heart illness about each moment in the United States alone. Specialists have been utilizing a few information mining strategies to assist wellbeing with caring experts in the conclusion of coronary illness. Anyway utilizing information mining procedure can decrease the quantity of test that is required. To diminish number of deaths from heart disease there must be a fast and proficient recognition strategy. Choice Tree is one of the compelling information mining strategies utilized. This exploration analyzes various calculations of Decision Tree characterization looking for better execution in coronary illness conclusion utilizing WEKA. The calculations which are tried is J48 calculation, Logistic model tree calculation and Random Forest calculation. The current datasets of coronary illness patients from Cleveland information base of UCI storehouse is utilized to test and legitimize the exhibition of choice tree calculations. This datasets comprises of 303 occurrences and 76 characteristics. Thusly, the order calculation that has ideal potential will be recommended for use in sizeable information. The objective of this study is to remove stowed away examples by applying information mining strategies, which are vital to heart sicknesses and to foresee the presence of coronary illness in patients where this presence is esteemed from no presence to likely presence.

Data Mining; Decision Support System; Health care; Health records; Classification.

"HEART DISEASE PREDICTION USING MACHINE LEARNING AND DATA MINING TECHNIQUE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 9, page no.12-19, September-2022, Available :http://www.jetir.org/papers/JETIRFS06002.pdf

"HEART DISEASE PREDICTION USING MACHINE LEARNING AND DATA MINING TECHNIQUE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 9, page no. pp12-19, September-2022, Available at : http://www.jetir.org/papers/JETIRFS06002.pdf