Scalable Parallel Clustering Approach for Large Data Using Possibilistic Fuzzy C-Means Algorithm

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
Clustering is an unsupervised learning task where one seeks to identify a finite set of categories termed clusters to describe the data. The proposed system, try to exploit computational power from the multi-core processors by modifying the design on existing algorithms and software. However, the existing clustering algorithms either handle different data types with inefficiency in handling large data or handle large data with limitations in considering numeric attributes. Hence, parallel clustering has come into picture to provide crucial contribution towards clustering large data.
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