Fuzzy cluster validation index based on inter-cluster proximity
Pattern Recognition Letters
Linearized cluster assignment via spectral ordering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
K-means clustering via principal component analysis
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Fuzzy PCA-guided robust k-means clustering
IEEE Transactions on Fuzzy Systems
Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications
Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications
Several formulations for graded possibilistic approach to fuzzy clustering
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Fuzzy c-means clustering of incomplete data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
Regularized Linear Fuzzy Clustering and Probabilistic PCA Mixture Models
IEEE Transactions on Fuzzy Systems
A Possibilistic Fuzzy c-Means Clustering Algorithm
IEEE Transactions on Fuzzy Systems
Soft transition from probabilistic to possibilistic fuzzy clustering
IEEE Transactions on Fuzzy Systems
Linear Fuzzy Clustering With Selection of Variables Using Graded Possibilistic Approach
IEEE Transactions on Fuzzy Systems
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Cluster validation is an important issue in fuzzy clustering research and many validity measures, most of which are motivated by intuitive justification considering geometrical features, have been developed. This paper proposes a new validation approach, which evaluates the validity degree of cluster partitions from the view point of the optimality of objective functions in FCM-type clustering. This approach makes it possible to evaluate the validity degree of robust cluster partitions, in which geometrical features are not available because of their possibilistic natures.