A Fast Fuzzy Based Unsupervised Classification: Using D & C Approach for Mixed Large Data Attributes

The clustering or unsupervised classification has variety of requirements in which the major one is the capability of the chosen clustering approach to deal with scalability and to handle with the mixed variety of data set. The present scenario of variety of latest approaches of unsupervised classification are swarm optimization based, customer segmentation based, soft computing methods like GA based, entropy based and fuzzy based methods and hierarchical approaches have two serious bottlenecks. Either, they are hybrid mathematical techniques or large computation demanding which increases their complexity and hence compromises with accuracy.

Provided by: International forum of researchers Students and Academician Topic: Data Management Date Added: Aug 2014 Format: PDF

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