Diabetes Prediction Medicament using Optimized SVM algorithm with Outlier detection and removal

被引：0

作者：

Kanmani, K. ^{[1
,2
]}

Murugan, A. ^{[3
]}

机构：

[1] Dr Ambedkar Govt Arts Coll, Chennai 600039, Tamil Nadu, India

[2] SRM Inst Sci & Technol, Coll Sci & Humanities, Dept Comp Applicat, Chennai 603203, TN, India

[3] Dr Ambedkar Govt ArtsColl Autonomous, PG & Res Dept Comp Sci, Chennai 600039, TN, India

来源：

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2022年 / 22卷 / 05期

关键词：

Data mining; SVM; Outlier Detection; R programming;

D O I：

10.22937/IJCSNS.2022.22.5.74

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Data mining-based prediction techniques can help in the early detection of diabetes and the related critical events. Data mining algorithms are being used to improve the early diagnosis of diseases such as type 2 diabetes. This study aims to develop an Optimized Prediction Model that can predict the risk of diabetes. In this work we are using an optimized SVM with applied outlier detection removal mechanism based on the input factors from individuals, we implemented this process by Using R Programming.

引用

页码：539 / 544

页数：6

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