Hyper-Graph Based Documents Categorization on Knowledge from Decision Trees
This document has devised a novel representation that compactly captures a Hyper-graph Partitioning and Clustering of the documents based on the weightages. The approach we take integrates data mining and decision making to improve the effectiveness of the approach, we also present a NeC4.5 decision trees. This algorithm is creating the cluster and sub clusters according to the user query. This project is forming sub clustering in the database. Some of the datas in the database may be efficient one, so we are clustering the datas depending upon the ability.
Keywords: Hyper-graph agglomerate algorithm, Clustering, Data Mining, NeC4.5 decision trees.
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ABOUT THE AUTHOR
Merjulah Roby
Lecturer in Lowry Memorial College
Merjulah Roby
Lecturer in Lowry Memorial College