Abstract
One crucial tool in machine learning is a measure of partition similarity. This study focuses on the “probabilistic Rand index”, a variant of the Rand index. We look at this measure from different perspectives: probabilistic, information-theoretic, and diversity-theoretic. These give some insight, reveal relationships with other types of measures, and suggest some possible alternative interpretations.
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