Prediction of heart disease using forest algorithm over linear regression algorithm using machine learning with improved accuracy

Cardiometry

article

K N S Shanmukha Raj¹  K Thinakaran¹ 

[1] Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University

关键词: Algorithm;    Linear Regression Algorithm;    Predicting Heart Disease;    Machine Learning;    Supervised Classification;    Novel Dimensionality Reduction;   

DOI  :  10.18137/cardiometry.2022.25.15071513

学科分类：环境科学（综合）

来源: Russian New University

【 摘 要 】

Aim: To perform Predicting heart disease using the Forest algorithm and comparing its feature extraction precision with the Linear Regression Algorithm for improving the accuracy of the prediction. Methods and Materials : In the proposed work, Predicting heart disease was carried out using machine learning algorithms such as Linear Regression (n=10)and Forest algorithm(n=10). Here the pretest power analysis was carried out with 80% and the sample size for the two groups are 20. Results: From The implemented experiment, the Forest algorithm accuracy is 90.32% and the Linear Regression Algorithm 77.21%. There is a statistical 2-tailed significant difference in accuracy for two algorithms is 0.001 (p<0.05) Conclusion:This study concludes that the Forest algorithm on patients healthcare analysis is significantly better than the Linear Regression Algorithm.

【 授权许可】

CC BY