Implementation of Various Machine Learning Algorithms for Heart Attack Prediction

Rajesh Rahangdale; Kranti Kumar Dewangan

Implementation of Various Machine Learning Algorithms for Heart Attack Prediction

Authors: Rajesh Rahangdale, Kranti Kumar Dewangan

Unique Paper ID: 155994
Volume: 9
Issue: 2
PageNo: 742-746

Keywords: Heart Disease Machine Learning Algorithms KNN Random Forest method and Logistic Regression.

Abstract:
The Heart Disease as exhibited by the diagram is the guideline wellspring of death any place on the world. The flourishing locale has an immense heap of information, yet despicably, this information is not overall around used. This is an immediate consequence of nonattendance of persuading evaluation mechanical congregations to find striking models in information. Information Mining can assist with recovering critical information from open information. It assists with arranging model to foresee patients' flourishing which will be quicker showed up contrastingly according to clinical trial and error. An enormous heap of examination has been done utilizing the Different Heart datasets. Different Implementation of AI calculations like K-Nearest Neighbor, Support Vector Machine, Logistic Regression, and soon have been applied. This assessment is on a very basic level looking for the capable computations that will work totally on coronary ailment. We will examine different computations on a given dataset and notice the entire preliminary achieve our work.

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Cite This Article

ISSN: 2349-6002
Volume: 9
Issue: 2
PageNo: 742-746

Implementation of Various Machine Learning Algorithms for Heart Attack Prediction

Available:https://ijirt.org/Article?manuscript=155994

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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