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Incremental Rough Possibilistic K-Modes.

, , and . MIWAI, volume 8271 of Lecture Notes in Computer Science, page 13-24. Springer, (2013)

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Semi-supervised Rough Cost/Benefit Decisions., , and . Fundam. Informaticae, 94 (2): 233-244 (2009)Analysis of User-Weighted π Rough k-Means., and . RSKT, volume 8818 of Lecture Notes in Computer Science, page 547-556. Springer, (2014)Towards Implementing Valuation Based Systems with Relational Databases., , and . ISMIS, volume 542 of Lecture Notes in Computer Science, page 172-182. Springer, (1991)Decremental Rough Possibilistic K-Modes., , and . ICAIS, volume 8779 of Lecture Notes in Computer Science, page 50-59. Springer, (2014)Genetic algorithms for rerouting shortest paths in dynamic and stochastic networks., and . Eur. J. Oper. Res., 144 (1): 27-38 (2003)Interpretation of Belief Functions in The Theory of Rough Sets., and . Inf. Sci., 104 (1-2): 81-106 (1998)Fuzzy-rough and rough-fuzzy serial combinations in neurocomputing.. Neurocomputing, 36 (1-4): 29-44 (2001)Propagation of knowledge from crisp and soft clustering through a granular hierarchy., , , , and . HIS, page 6-11. IEEE, (2012)Rough Cluster Quality Index Based on Decision Theory., , and . IEEE Trans. Knowl. Data Eng., 21 (7): 1014-1026 (2009)Clustering Ensemble for Prioritized Sampling Based on Average and Rough Patterns., , , , and . ISMIS, volume 10352 of Lecture Notes in Computer Science, page 530-539. Springer, (2017)