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We review two clustering algorithms (hard c-means and single linkage) and three indexes of crisp cluster validity (Hubert's statistics, the Davies-Bouldin index, and Dunn's index). We illustrate two deficiencies of Dunn's index which make it overly sensitive to noisy clusters and propose several generalizations of it that are not as brittle to outliers in(More)
Many functionals have been proposed for validation of partitions of object data produced by the fuzzy c-means (FCM) clustering algorithm. We examine the role a subtle but important parameter-the weighting exponent m of the FCM model-plays in determining the validity of FCM partitions. The functionals considered are the partition coefficient and entropy(More)
The relationship between the sequential hard c-means (SHCM) and learning vector quantization (LVQ) clustering algorithms is discussed. The impact and interaction of these two families of methods with Kohonen's self-organizing feature mapping (SOFM), which is not a clustering method but often lends ideas to clustering algorithms, are considered. A(More)
The feedforward multilayer perceptron (MLP) with back-propagation of error is described. Since use of this network requires a set of labeled input-output, as such it cannot be used for segmentation of images when only one image is available. (However, if images to be processed are of similar nature, one can use a set of known images for learning and then(More)