Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Data Mining and Knowledge Discovery Handbook
Data Mining and Knowledge Discovery Handbook
Pattern Recognition Letters
Extending the rand, adjusted rand and jaccard indices to fuzzy partitions
Journal of Intelligent Information Systems
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Comparing fuzzy, probabilistic, and possibilistic partitions
IEEE Transactions on Fuzzy Systems
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The Rand index is a measure commonly used to compare crisp partitions. Campello (2007) and Hüllermeier and Rifqi (2009) respectively, proposed two extensions of this index capable to compare fuzzy partitions. These approaches are useful when continuous values of attributes are discretized using fuzzy sets. In previous works we experimented with these extensions and compared their accuracy with the one of the crisp Rand index. In this paper we propose the ε-procedure, an alternative way to deal with attributes taking continuous values. Accuracy results on some known datasets of the Machine Learning repository using the ε-procedure as crisp discretization method jointly with the crisp Rand index are comparable to the ones given using the crisp Rand index and its fuzzifications with standard crisp and fuzzy discretization methods respectively.