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Suleman, A. (2017). Assessing a fuzzy extension of Rand index and related measures. IEEE Transactions on Fuzzy Systems. 25 (1), 237-244
A. K. Suleman, "Assessing a fuzzy extension of Rand index and related measures", in IEEE Transactions on Fuzzy Systems, vol. 25, no. 1, pp. 237-244, 2017
@article{suleman2017_1714127523816, author = "Suleman, A.", title = "Assessing a fuzzy extension of Rand index and related measures", journal = "IEEE Transactions on Fuzzy Systems", year = "2017", volume = "25", number = "1", doi = "10.1109/TFUZZ.2016.2554155", pages = "237-244", url = "http://ieeexplore.ieee.org/abstract/document/7452581/" }
TY - JOUR TI - Assessing a fuzzy extension of Rand index and related measures T2 - IEEE Transactions on Fuzzy Systems VL - 25 IS - 1 AU - Suleman, A. PY - 2017 SP - 237-244 SN - 1063-6706 DO - 10.1109/TFUZZ.2016.2554155 UR - http://ieeexplore.ieee.org/abstract/document/7452581/ AB - This empirical study extends the results of Hu?llermeier, Rifqi, Henzgen, and Senge (2012). It examines the ability of a generalization of the Rand index and four related measures of similarity to recover the cluster structure of the data in the framework of fuzzy c-means clustering. The index range is also used as a criterion statistic. A Monte Carlo simulation is conducted for both the null case and where the data have a well-defined cluster structure. The fuzzy extension of the related measures is not so effective for imbalanced data. On the contrary, whether the index is Dice, Fowlkes and Mallows, Hurbert and Arabie, or Jaccard, it provides reliable results for noise data or for data containing fairly balanced clusters. The criticisms of the Rand index in the context of crisp clustering can also be extended to its fuzzy version. ER -