On the Equivalence of Cohen's Kappa and the Hubert-Arabie Adjusted Rand Index
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It is shown that one can calculate the Hubert-Arabie adjusted Rand index by first forming the fourfold contingency table counting the number of pairs of objects that were placed in the same cluster in both partitions.Abstract:
It is shown that one can calculate the Hubert-Arabie adjusted Rand index by first forming the fourfold contingency table counting the number of pairs of objects that were placed in the same cluster in both partitions, in the same cluster in one partition but in different clusters in the other partition, and in different clusters in both, and then computing Cohen's ? on this fourfold table.read more
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References
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Journal ArticleDOI
A Coefficient of agreement for nominal Scales
TL;DR: In this article, the authors present a procedure for having two or more judges independently categorize a sample of units and determine the degree, significance, and significance of the units. But they do not discuss the extent to which these judgments are reproducible, i.e., reliable.
Journal ArticleDOI
Objective Criteria for the Evaluation of Clustering Methods
TL;DR: This article proposes several criteria which isolate specific aspects of the performance of a method, such as its retrieval of inherent structure, its sensitivity to resampling and the stability of its results in the light of new data.
Journal Article
A statistical method for evaluating systematic relationships
Journal ArticleDOI
A Method for Comparing Two Hierarchical Clusterings
TL;DR: The derivation and use of a measure of similarity between two hierarchical clusterings, Bk, is derived from the matching matrix, [mij], formed by cutting the two hierarchical trees and counting the number of matching entries in the k clusters in each tree.
Journal ArticleDOI
Metric and Euclidean properties of dissimilarity coefficients
John C. Gower,Pierre Legendre +1 more
TL;DR: In this paper, the authors present properties of dissimilarity coefficients with respect to their metric and Euclidean status, and the response to different types of data is investigated, leading to guidance on the choice of an appropriate coefficient.