Expert Systems with Applications: An International Journal
A survey of kernel and spectral methods for clustering
Pattern Recognition
Fuzzy neural network structure identification based on soft competitive learning
International Journal of Hybrid Intelligent Systems
Kernelized fuzzy attribute C-means clustering algorithm
Fuzzy Sets and Systems
Fuzzy one-class support vector machines
Fuzzy Sets and Systems
A Kernel-Based Two-Stage One-Class Support Vector Machines Algorithm
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Pattern recognition using neural-fuzzy networks based on improved particle swam optimization
Expert Systems with Applications: An International Journal
A new maximal-margin spherical-structured multi-class support vector machine
Applied Intelligence
A kernelized fuzzy c-means algorithm for automatic magnetic resonance image segmentation
Journal of Computational Methods in Sciences and Engineering
From minimum enclosing ball to fast fuzzy inference system training on large datasets
IEEE Transactions on Fuzzy Systems
Clustering: A neural network approach
Neural Networks
Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study
Fuzzy Sets and Systems
On support vector regression machines with linguistic interpretation of the kernel matrix
Fuzzy Sets and Systems
Rapid and brief communication: Rough support vector clustering
Pattern Recognition
A new multi-class support vector machine with multi-sphere in the feature space
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Information Sciences: an International Journal
MMSVC: an efficient unsupervised learning approach for large-scale datasets
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and simulation and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part III
A kernel prototype-based clustering algorithm
ICCOMP'06 Proceedings of the 10th WSEAS international conference on Computers
DBCAMM: A novel density based clustering algorithm via using the Mahalanobis metric
Applied Soft Computing
Deterministic annealing multi-sphere support vector data description
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part III
Support vector description of clusters for content-based image annotation
Pattern Recognition
Kernel fuzzy c-means with automatic variable weighting
Fuzzy Sets and Systems
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In this paper, the support vector clustering is extended to an adaptive cell growing model which maps data points to a high dimensional feature space through a desired kernel function. This generalized model is called multiple spheres support vector clustering, which essentially identifies dense regions in the original space by finding their corresponding spheres with minimal radius in the feature space. A multisphere clustering algorithm based on adaptive cluster cell growing method is developed, whereby it is possible to obtain the grade of memberships, as well as cluster prototypes in partition. The effectiveness of the proposed algorithm is demonstrated for the problem of arbitrary cluster shapes and for prototype identification in an actual application to a handwritten digit data set.