An Information-Theoretic External Cluster-Validity Measure

An Information-Theoretic External Cluster-Validity Measure (2001)

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by Byron E. Dom , Byron E. Dom

Venue:	Research Report RJ 10219, IBM
Citations:	48 - 2 self

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Datum	Value	Source
TITLE	An information-theoretic external cluster-validity measure	INFERENCE
AUTHOR NAME	Byron E. Dom	SVM HeaderParse 0.1
AUTHOR AFFIL	ABSTRACT:	SVM HeaderParse 0.2
AUTHOR ADDR	Yorktown Heights, New York ffl San Jose, California ffl Zurich, Switzerland	SVM HeaderParse 0.1
AUTHOR NAME	Byron E. Dom	SVM HeaderParse 0.1
AUTHOR AFFIL	ABSTRACT:	SVM HeaderParse 0.2
AUTHOR ADDR	Yorktown Heights, New York ffl San Jose, California ffl Zurich, Switzerland	SVM HeaderParse 0.2
ABSTRACT	In this paper we propose a measure of similarity/association between two partitions of a set of objects. Our motivation is the desire to use the measure to characterize the quality or accuracy of clustering algorithms by somehow comparing the clusters they produce with "ground truth" consisting of classes assigned to the patterns by manual means or some other means in whose veracity there is confidence. Such measures are referred to as "external". Our measure also allows clusterings with different numbers of clusters to be compared in a quantitative and principled way. Our evaluation scheme quantitatively measures how useful the cluster labels of the patterns are as predictors of their class labels. When all clusterings to be compared have the same number of clusters, the measure is equivalent to the mutual information between the cluster labels and the class labels. In cases where the numbers of clusters are different, however, it computes the reduction in the number of bits that w...	user correction - Legacy Corrections
YEAR	2001	INFERENCE
VENUE	Research Report RJ 10219, IBM	INFERENCE
VENUE TYPE	TECHREPORT	INFERENCE
TECH	Technical Report RJ10219, IBM	INFERENCE
CITATIONS	21 found	ParsCit 1.0