Journal ArticleDOI
A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
J. C. Dunn
- Vol. 3, Iss: 3, pp 32-57
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TLDR
Two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space; in both cases, the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the least squarederror criterion function.Abstract:
Two fuzzy versions of the k-means optimal, least squared error partitioning problem are formulated for finite subsets X of a general inner product space. In both cases, the extremizing solutions are shown to be fixed points of a certain operator T on the class of fuzzy, k-partitions of X, and simple iteration of T provides an algorithm which has the descent property relative to the least squared error criterion function. In the first case, the range of T consists largely of ordinary (i.e. non-fuzzy) partitions of X and the associated iteration scheme is essentially the well known ISODATA process of Ball and Hall. However, in the second case, the range of T consists mainly of fuzzy partitions and the associated algorithm is new; when X consists of k compact well separated (CWS) clusters, Xi , this algorithm generates a limiting partition with membership functions which closely approximate the characteristic functions of the clusters Xi . However, when X is not the union of k CWS clusters, the limi...read more
Citations
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Fuzzy C-means algorithm based on standard mahalanobis distances
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Partitive clustering ( K -means family)
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GSM churn management by using fuzzy c-means clustering and adaptive neuro fuzzy inference system
Adem Karahoca,Dilek Karahoca +1 more
TL;DR: Adaptive Neuro Fuzzy Inference System (ANFIS) is executed to develop a sensitive prediction model for churn management by using Neuro fuzzy classifiers' outputs as input to make a decision about churners' activities.
Journal ArticleDOI
Comparison of two fuzzy algorithms in geodemographic segmentation analysis: The Fuzzy C-Means and Gustafson–Kessel methods
TL;DR: The main objective of this paper is to evaluate the performance of the Fuzzy C-Means and Gustafson–Kessel algorithms in the clustering problem, under specific conditions.