Open AccessHeart Attack Prediction with Hybrid Technique of Weighted K-Mean and Logistic Regression
Author(s) -
Rupinder Kaur,
Gaurav Gupta
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b3589.079220
Subject(s) - logistic regression , computer science , precision and recall , field (mathematics) , recall , artificial intelligence , analytics , data mining , regression analysis , regression , point (geometry) , machine learning , statistics , pattern recognition (psychology) , mathematics , psychology , geometry , pure mathematics , cognitive psychology
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%.