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Construction of the Ensemble of Logical Models in Cluster Analysis

机译:聚类分析中逻辑模型集合的构建

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摘要

In this paper, the algorithm of cluster analysis based on the ensemble of tree-like logical models (decision trees) is proposed. During the construction of the ensemble, the algorithm takes into account distances between logical statements describing clusters. Besides, we consider some properties of the Bayes model of classification. These properties are used at the motivation of information-probabilistic criterion of clustering quality. The results of experimental studies demonstrate the effectiveness of the suggested algorithm.
机译:本文提出了一种基于树状逻辑模型(决策树)集成的聚类分析算法。在构建集成体时,该算法会考虑描述聚类的逻辑语句之间的距离。此外,我们考虑了贝叶斯分类模型的一些性质。这些属性用于激励信息概率标准的聚类质量。实验研究的结果证明了该算法的有效性。

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