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Hinging hyperplane based regression tree identified by fuzzy clustering and its application
2013
Applied Soft Computing
Hierarchical fuzzy modeling techniques have great advantage since model accuracy and complexity can be easily controlled thanks to the transparent model structures. A novel tool for regression tree identification is proposed based on the synergistic combination of fuzzy c-regression clustering and the concept of hierarchical modeling. In a special case (c = 2), fuzzy c-regression clustering can be used for identification of hinging hyperplane models. The proposed method recursively identifies a
doi:10.1016/j.asoc.2012.09.027
fatcat:yksxhnrhnrbwxksncl2ndengoi