计算机科学 ›› 2011, Vol. 38 ›› Issue (1): 221-224.
• 人工智能 • 上一篇 下一篇
于洪,储双双
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基金资助:
YU Hong,CHU Shuang-shuang
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摘要: 提出了一种基于决策粗糙集的面向知识的自动聚类方法。在面向知识的聚类算法中,获取初始聚类结果依赖人工阂值的设置。为此,首先根据物理学知识提出了一种差值排序方法来自动得到阂值。另外,讨论了决策粗糙集模型的损失函数,提出了一种聚类评佑方法;通过对聚类结果的评佑来实现自动聚类。实验结果表明新方法是有效的。
关键词: 聚类,面向知识,决策粗糙集,自动
Abstract: This paper proposed an autonomous knowledge-oriented clustering method based on decision-theoretic rough set model. In order to obtain the initial clustering, the initial threshold values need to set in the knowledgcoricnted clustering framework. Thus, a novel method, sort difference, was proposed to produce the initial threshold values autonomously in view of physics theory. Then, a cluster validity index based on the decision-theoretic rough set model was developed by considering various loss functions, which can estimate the quality of clustering.The results of experiments show that the new approach is valuable.
Key words: Clustering, Knowledge-oriented, Decision-theoretic rough set, Autonomous
于洪,储双双. 一种基于决策粗糙集的自动聚类方法[J]. 计算机科学, 2011, 38(1): 221-224. https://doi.org/
YU Hong,CHU Shuang-shuang. Novel Autonomous Clustering Method Based on Decision-theoretic Rough Set[J]. Computer Science, 2011, 38(1): 221-224. https://doi.org/
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