Heart Attack Prediction with Hybrid Technique of Weighted K-Mean and Logistic Regression
Rupinder kaur1, Gaurav Gupta2

1Rupinder kaur, Computer Engineering Department, Punjabi University Patiala.
2Dr. Gaurav Gupta , Computer Engineering Department ,Punjabi University Patiala.

Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 445-448 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3589079220/2020©BEIESP | DOI: 10.35940/ijrte.B3589.079220
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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: Data analytics is the main focusing point for different fields. Medical field is the new entrant to the data analytics. It specifically picks the data related to patient different parameters and evaluates the parameters with different machine learning algorithms. In proposed technique the heart attack prediction based on different parameters has been evaluated. These parameters are related to patient different aspects like blood pressure, blood sugar, age, physical activities etc. The proposed technique for the prediction is k-mean and logistic regression. The proposed technique is showing better results in terms of accuracy, precision and recall. The accuracy improvement is around 1.67%, Recall is improved by 1.15% and precision is improved by 3.15%. 
Keywords: Prediction, Logistic regression, k-mean