聚类分析
计算机科学
层次聚类
欧几里得空间
星团(航天器)
欧几里德几何
欧几里德距离
文档聚类
数据挖掘
人工智能
理论(学习稳定性)
模式识别(心理学)
数学
机器学习
组合数学
几何学
程序设计语言
标识
DOI:10.1007/978-3-030-17705-8_2
摘要
Usually, text documents are represented as a vector of n-dimensional Euclidean space. One of the main it the problem of the typology of texts using cluster analysis is to determine the number of clusters. In this article was researched the agglomerative clustering algorithm in Euclidean space. A statistical criterion for completing the clustering process was deriving as the Markov moment. Was considered the problem of cluster stability. As an example, it was considered retrieval of the harmful content.
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