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基于强化学习的LVQ聚类方法
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作者 程小平 邱玉辉 《计算机科学》 CSCD 北大核心 2002年第12期133-134,132,共3页
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 d... 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. 展开更多
关键词 机器学习 强化学习 数据挖掘 lvq聚类方法 神经网络
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