Analysis and comparison for prediction of Diabetic Pregnant women using Innovative Principal Component Analysis algorithm over Support Vector Machine Algorithm with Improved Accuracy

Cardiometry

article

Venkata Sai Kumar Pokala¹  Neelam Sanjeev Kumar¹ 

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

关键词: Diabetes prediction;    Innovative Principal Component Analysis algorithm;    Support Vector Machine algorithm;    Artificial Intelligence;    Accuracy;   

DOI  :  10.18137/cardiometry.2022.25.942948

学科分类：环境科学（综合）

来源: Russian New University

【 摘 要 】

0.05), a sensitivity of 79.29% with P=0.096 (p<0.05), and a precision of 83.57%. Support Vector Machine algorithm results in mean accuracy of 77.67%, a sensitivity of 76.67%, and a precision of 83.54%. Conclusion: Principal Component Analysis algorithm performed significantly better than the Support Vector Machine algorithm for Diabetic prediction.

【 授权许可】

CC BY