Application of Bagging and Boosting Approaches Using Decision Tree-Based Algorithms in Diabetes Risk Prediction

Application of Bagging and Boosting Approaches Using Decision Tree-Based Algorithms in Diabetes Risk Prediction

Diabetes is a serious condition that leads to high blood sugar and the prediction of this disease at an early stage is of great importance for reducing the risk of some significant diabetes complications. In this study, bagging and boosting approaches using six different decision tree-based (DTB) cl...

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Bibliographic Details
Main Author: Pelin Yildirim Taser
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Proceedings
Subjects:
diabetes prediction
machine learning
ensemble learning
classification
decision tree-based algorithms
Online Access:https://www.mdpi.com/2504-3900/74/1/6

Internet

https://www.mdpi.com/2504-3900/74/1/6

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