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• W3091999632 abstract "The misclassification error distance and the adjusted Rand index are two of the most common criteria used to evaluate the performance of clustering algorithms. This paper provides an in-depth comparison of the two criteria, with the aim of better understand exactly what they measure, their properties and their differences. Starting from their population origins, the investigation includes many data analysis examples and the study of particular cases in great detail. An exhaustive simulation study provides insight into the criteria distributions and reveals some previous misconceptions." @default.
• W3091999632 created "2020-10-15" @default.
• W3091999632 creator A5066580481 @default.
• W3091999632 date "2020-10-08" @default.
• W3091999632 modified "2023-10-18" @default.
• W3091999632 title "A close‐up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation" @default.
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• W3091999632 doi "https://doi.org/10.1111/bmsp.12212" @default.
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