Selecting Parameter Values for Mahalanobis Distance Fuzzy Classifiers
Abstract
The fuzzy c-means clustering algorithm, and a related supervised classifier, require the a priori selection of a weighting parameter called the fuzzy exponent. This paper investigates suitable values of this fuzzy exponent using the criterion that fuzzy set memberships reflect class proportions in the mixed pixels of a remotely sensed image
Conference Title
Proceedings of the 10th IEEE International Conference on Fuzzy Systems
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