Comparing high dimensional partitions with the Coclustering Adjusted Rand Index

Valérie Robert 1, 2 Yann Vasseur 1, 2
2 SELECT - Model selection in statistical learning
Inria Saclay - Ile de France, LMO - Laboratoire de Mathématiques d'Orsay, CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : The popular Adjusted Rand Index (ARI) is extended to the task of simultaneous clustering of the rows and columns of a given matrix. This new index called Coclustering Adjusted Rand Index (CARI) remains convenient and competitive facing other indices. Indeed, partitions with high numbers of clusters can be considered and it does not require any convention when the numbers of clusters in partitions are different. Experiments on simulated partitions are presented and the performance of this index to measure the agreement between two pairs of partitions is assessed. Comparison with other indices is discussed.
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Pré-publication, Document de travail
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Soumis le : mercredi 31 mai 2017 - 11:42:24
Dernière modification le : mardi 17 avril 2018 - 09:04:15


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  • HAL Id : hal-01524832, version 3


Valérie Robert, Yann Vasseur. Comparing high dimensional partitions with the Coclustering Adjusted Rand Index. 2017. 〈hal-01524832v3〉



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