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Fuzzy c-means clustering (FCM) algorithm is an important and basic tool of classification and analysis for no supervision data, which has been used extensively in pattern recognition, data analysis, image processing and fuzzy modeling. Although the FCM algorithm is an unsupervised machine self-learning algorithm, however, there are two parameters must be given appropriate assignment before conducting...
Clustering is a widely used to discover underlying patterns and groups in data and there is a need to validate the quality of clusters generated by the numerous clustering algorithms in use. The need for cluster validitation arises from the fundamental definition of unsupervised learning. As clustering is an unsupervised learning process, the prediction of correct number of clusters is a hurdle which...
The cluster analysis deals with the problems of organization of a collection of data objects into clusters based on similarity. It is also known as the unsupervised classification of objects and has found many applications in different areas. An important component of a clustering algorithm is the distance measure which is used to find the similarity between data objects. K-means is one of the most...
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