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Design analysis and implementation of efficient parameter free algorithm for high quality homogeneous clusters in data mining applications

机译:数据挖掘应用中高质量同质集群高效无参数算法的设计分析与实现

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A new algorithm for clustering high-dimensional categorical data is proposed and implemented by us. Our algorithm is parameter-free, fully-automatic and is based on a two-phase iterative procedure. In the first phase, cluster assignments are given, and a
机译:我们提出并实现了一种新的聚类高维分类数据的算法。我们的算法是无参数的,全自动的,并且基于两阶段迭代过程。在第一阶段,给出了集群分配,并且

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