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Information Technology Journal
  Year: 2009 | Volume: 8 | Issue: 2 | Page No.: 173-180
DOI: 10.3923/itj.2009.173.180
 
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Integrated Approach of Reduct and Clustering for Mining Patterns from Clusters

A. Arora, S. Upadhyaya and R. Jain

Abstract:
In this study, a method is presented for selection and ranking of significant attributes for individual clusters which lead to formulation of concise and user understandable patterns. Cluster is set of similar data objects and similarity is measured on attribute values. Attributes which have same value for majority of objects in a cluster are considered significant and rest non significant for that cluster. Reduct from rough set theory is defined as the set of attributes which distinguishes the objects in a homogenous cluster, therefore these can be clear cut removed from the same. Non reduct attributes are ranked for their contribution in the cluster. Pattern is then formed by conjunction of most contributing attributes of that cluster.
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How to cite this article:

A. Arora, S. Upadhyaya and R. Jain, 2009. Integrated Approach of Reduct and Clustering for Mining Patterns from Clusters. Information Technology Journal, 8: 173-180.

DOI: 10.3923/itj.2009.173.180

URL: https://scialert.net/abstract/?doi=itj.2009.173.180

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