A Approach in Fuzzy Sets for Feature Reduction
Pattern representation refers to the number of classes, the number of available patterns, the number, type and scale of the features available to clustering algorithms. Pattern proximity is usually measured by a distance function defined on pairs of patterns. A variety of distance functions are in use in various communities. The Grouping step represents the organization of patterns into clusters based on pattern similarity. There are many clustering methods available, and each of them may give a different grouping of a dataset. The choice of a particular method will depend on the type of output desired, the known performance of method with particular types of data, the hardware and software facilities available and the size of the dataset .
Keywords - Pattern proximity, Clustering, Distance functions.