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基于强化学习的LVQ聚类方法

Reinforcement Learning Based LVQ Clustering Approach
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摘要 A reinforcement clustering framework which constitutes Bernoulli stochastic neural units is proposed inthis paper. Reinforcement learning mechanism is introduced to LVQ clustering problems. Related algorithm LVQ-Ris developed and its property is analyzed in detail. The authors conclude that reinforcement learning can be also intro-duced to other on-line competitive clustering methods. Experiments show that LVQ-R has better performance than o-riginal LVQ approach. A reinforcement clustering framework which constitutes Bernoulli stochastic neural units is proposed in this paper. Reinforcement learning mechanism is introduced to LVQ clustering problems. Related algorithm LVQ-R is developed and its property is analyzed in detail. The authors conclude that reinforcement learning can be also introduced to other on-line competitive clustering methods. Experiments show that LVQ-R has better performance than o-riginal LVQ approach.
出处 《计算机科学》 CSCD 北大核心 2002年第12期133-134,132,共3页 Computer Science
关键词 机器学习 强化学习 数据挖掘 LVQ聚类方法 神经网络 Reinforcement learning, Bernoulli stochastic unit, LVQ
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