Comparing clusterings by the variation of information
Comparing clusterings by the variation of information
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DOI：
10.1007/978-3-540-45167-9_14
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发表时间：
2003-01-01
期刊：
影响因子：
--
通讯作者：
Meila, M
中科院分区：
文献类型：
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作者：
Meila, M
本文提出了一个信息论标准比较两个分区，或聚类，同一数据集。该标准称为信息变化（VI），测量从聚类C到聚类C '的变化中丢失和获得的信息量。该标准没有假设聚类是如何产生的，并适用于软聚类和硬聚类。从比较聚类的角度给出并讨论了VI的基本性质。特别地，VI是正的、对称的并且服从三角不等式。因此，令人惊讶的是，它是聚类空间的真实度量。
This paper proposes an information theoretic criterion for comparing two partitions, or clusterings, of the same data set. The criterion, called variation of information (VI), measures the amount of information lost and gained in changing from clustering C to clustering C'. The criterion makes no assumptions about how the clusterings were generated and applies to both soft and hard clusterings. The basic properties of VI are presented and discussed from the point of view of comparing clusterings. In particular, the VI is positive, symmetric and obeys the triangle inequality. Thus, surprisingly enough, it is a true metric on the space of clusterings.