The design and analysis of spatial data structures
The design and analysis of spatial data structures
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
A fuzzy modeling method via Enhanced Objective Cluster Analysis for designing TSK model
Expert Systems with Applications: An International Journal
Grid-based clustering algorithm based on intersecting partition and density estimation
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
A framework for use of imprecise categorization in developing intelligent systems
IEEE Transactions on Fuzzy Systems
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A new clustering technique is described, which is an improvement on the mountain method (MM) of clustering originally proposed by Yager and Filev. This new technique employs a data driven, hierarchical partitioning of the data set to be clustered, using a "p-tree" algorithm for spatially decomposing the data set. The centroids of data subsets in the terminal nodes of the "p-tree" become the set of candidate cluster centers upon which the iterative cluster center selection process of MM is applied. As the data dimension and/or the number of uniform grid lines used in Yager and Filev's original technique increases, our approach requires exponentially fewer cluster centers to be evaluated by the MM selection algorithm. Extensive sample data sets are used to illustrate the performance of this new technique.