A Unified Theoretical Framework for Data Mining

The pattern extraction and discovery of useful information from a dataset are the foremost purposes of data mining; the outcome of this process is the ‘knowledge’ which is helpful in taking the decision. For the past decade there have been multiple attempts and strong beliefs in the development and...

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Bibliographic Details
Published in:Procedia computer science 2013, Vol.17, p.104-113
Main Authors: Khan, Dost Muhammad, Mohamudally, Nawaz, Babajee, D.K.R.
Format: Article
Language:English
Subjects:
Composite Function
Data Mining Algorithms
Datasets
Multiagent System (MAS)
Unified Data Mining Framework
Unified Data Mining Theory (UDMT)
Unified Theory (UT)
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Summary:The pattern extraction and discovery of useful information from a dataset are the foremost purposes of data mining; the outcome of this process is the ‘knowledge’ which is helpful in taking the decision. For the past decade there have been multiple attempts and strong beliefs in the development and the formulation of the unified data mining frameworks that would answer to the fundamental versions related to the discovery of knowledge. In this paper we are presenting a novel unified framework for data mining conceptualized through the composite functions. The framework is further illustrated with a variety of real life datasets using different data mining algorithms.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2013.05.015