Heart Disease Prediction using Machine Learning Algorithm
Journal: International Journal of Trend in Scientific Research and Development (Vol.5, No. 2)Publication Date: 2021-02-11
Authors : Ravi Kumar Singh A Rengarajan;
Page : 183-187
Keywords : Machine Learning; k-Nearest Neighbors classifier; Decision Tree classifier; Random Forest Classifier; Jupyter;
Abstract
Nowadays, Heart disease has become dangerous to a human being, it effects very badly to human body. If anyone is suffering from heart disease, then it leads to blood clotting. Heart disease prediction is very difficult task to predict in the field of medical science. Affiliation has predicted that 12 million people fail horrendously every year as a result of heart disease. In this paper, we propose a k Nearest Neighbors Algorithm KNN way to deal with improve the exactness of heart determination. We show that k Nearest Neighbors Algorithm KNN have better accuracy than random forest algorithm for viewing heart disease. The k Nearest Neighbors Algorithm give more precise and exact outcome . We have taken 13 attributes in the dataset and a target attribute, by applying machine learning we achieved 84 accuracy in the heart disease detection. Ravi Kumar Singh | Dr. A Rengarajan "Heart Disease Prediction using Machine Learning Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38358.pdf Paper Url: https://www.ijtsrd.com/computer-science/other/38358/heart-disease-prediction-using-machine-learning-algorithm/ravi-kumar-singh
Other Latest Articles
- Evaluation of Microbial Quality of Selected Herbal Raw Materials Marketed in Sri Lanka
- Socio Economic Status and Health Condition among the E Rickshaw Puller Drivers A Case Study
- Effects of Mirror Therapy MT and Modified Constraint Induced Movement Therapy on Improvement of Hand in Stroke Survivors A Comparative Study
- An Efficacy Study on Improving Balance in Subacute Stroke Patients by Proprioceptive Training with Additional Motor Imagery
- Synchronization and Reactive Current Support of PMSG Based Wind Farm during Severe Grid Fault
Last modified: 2021-04-09 16:23:06