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Updated: May 27, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

基于SMOTE和高斯混合模型的混合SMOTE和高斯混合模型优化了XGBoost框架,用于检测双相情感障碍

Santosh Kumar1, Deeksha Kumari1, Arvind Panwar2

  • 1School of Computing Science and Engineering, Galgotias University, Greater Noida, Uttar Pradesh, India.

Scientific reports
|March 3, 2026
PubMed
概括

这项研究引入了一种混合机器学习模型,用于准确识别双相情感障碍 (BD). 该框架通过整合数据平衡和子组发现来改善早期查和个性化治疗.

关键词:
双极性障碍是一种双极性障碍.高斯混合模型 (GMM)心理健康诊断 心理健康诊断 心理健康诊断在SMOTE中使用.在XGBoost中使用.

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