Heart Disease Prediction using Machine Learning Algorithms
Hrudi Sai Akhil Bommadevara1, Y. Sowmya2, G. Pradeepini3
1Bommadevara Hrudi Sai Akhil, Department of Computer Science and Engineering, KL University, Vaddeswaram (A.P), India.
2Sowmya Yalavarthi, Department of Computer Science and Engineering, KL University, Vaddeswaram (A.P), India.
3G.Pradeepini, Department of Computer Science and Engineering, KL University, Vaddeswaram (A.P), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 270-272 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3028038519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Machine learning is the sub branch of artificial intelligence and it is making computers to learn from data without being explicitly programmed Heart disease prediction is used to determine the root cause of getting heart attack and the probability of getting a heart attack, group the people into different clusters based on getting heart attack or not There are five levels in heart attack from level 0 to level 4. There are 14 important attributes to be considered in analysis of heart attack namely age, BP, CHOL, gender, CP, CA, THAL.
Keyword: Naïve Bayes, Decision Tree, Clustering, Linear Regression, Correlation.
Scope of the Article: Machine Learning