Clustering with Intelligent Techniques
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Cluster analysis is a technique for grouping data and finding structures in data. The most common application of clustering methods is to partition a data set into clusters or classes, where similar data are assigned to the same cluster whereas dissimilar data should belong to different clusters. In real-world applications there is very often no clear boundary between clusters so that fuzzy clustering is often a good alternative to use. Membership degrees between zero and one are used in fuzzy clustering instead of crisp assignments of the data to clusters.
KeywordsMembership Function Cluster Center Fuzzy Cluster Intelligent Technique Unsupervised Cluster
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