Application of the least trimmed squares technique to prototype-based clustering
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
On efficiency of optimization in fuzzy c-means
Neural, Parallel & Scientific Computations
Extreme physical information and objective function in fuzzy clustering
Fuzzy Sets and Systems - Clustering and modeling
Evolutionary semi-supervised fuzzy clustering
Pattern Recognition Letters
General C-Means Clustering Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Reinforcement Learning Approach to Online Clustering
Neural Computation
Global optimization in clustering using hyperbolic cross points
Pattern Recognition
Non-Euclidean c-means clustering algorithms
Intelligent Data Analysis
Analytical and Numerical Evaluation of the Suppressed Fuzzy C-Means Algorithm
MDAI '08 Sabadell Proceedings of the 5th International Conference on Modeling Decisions for Artificial Intelligence
A Scalable Framework For Segmenting Magnetic Resonance Images
Journal of Signal Processing Systems
On the efficiency of evolutionary fuzzy clustering
Journal of Heuristics
Data analysis with fuzzy clustering methods
Computational Statistics & Data Analysis
A generalized c-means clustering model using optimized via evolutionary computation
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Collaborative optimization of clustering by fuzzy c-means and weight determination by ReliefF
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Continuous value attribute decision table analysis method based on fuzzy set and rough set theory
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
A fuzzy c-means clustering algorithm based on nearest-neighbor intervals for incomplete data
Expert Systems with Applications: An International Journal
Fuzzy C-means and fuzzy swarm for fuzzy clustering problem
Expert Systems with Applications: An International Journal
Relational duals of cluster-validity functions for the c-means family
IEEE Transactions on Fuzzy Systems
A new evolutionary algorithm for image segmentation
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Data clustering using harmony search algorithm
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
Reformulating Learning Vector Quantization and Radial Basis Neural Networks
Fundamenta Informaticae
A genetic algorithm-based clustering and two-scan labelling for colour image segmentation
International Journal of Computational Vision and Robotics
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Various hard, fuzzy and possibilistic clustering criteria (objective functions) are useful as bases for a variety of pattern recognition problems. At present, many of these criteria have customized individual optimization algorithms. Because of the specialized nature of these algorithms, experimentation with new and existing criteria can be very inconvenient and costly in terms of development and implementation time. This paper shows how to reformulate some clustering criteria so that specialized algorithms can be replaced by general optimization routines found in commercially available software. We prove that the original and reformulated versions of each criterion are fully equivalent. Finally, two numerical examples are given to illustrate reformulation