Diffusion logistic regression algorithms over multiagent networks
Yan DU1
Lijuan JIA1
Shunshoku KANAE2
Zijiang YANG3
1.School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China2.Department of Medical Engineering, Faculty of Health Science, Junshin Gakune University, Fukuoka, Japan3.Department of Intelligent Systems Engineering, Ibaraki University, 4-12-1 Nakanarusawa, Hitachi, Ibaraki 316-8511, Japan
摘要：In this paper,a distributed scheme is proposed for ensemble learning method of bagging,which aims to address the classification problems for large dataset by developing a group of cooperative logistic regression learners in a connected network.Moveover,each weak learner/agent can share the local weight vector with its immediate neighbors through diffusion strategy in a fully distributed manner.Our diffusion logistic regression algorithms can effectively avoid overfitting and obtain high classification accuracy compared to the non-cooperation mode.Furthermore,simulations with a real dataset are given to demonstrate the effectiveness of the proposed methods in comparison with the centralized one.
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论文发表日期：2020-05-05
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：8( 160-167 )
英文信息