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Data clustering using maximum dependency of attributes and its application to cluster agricultural products

Hafiz Kamal, Leang (2012) Data clustering using maximum dependency of attributes and its application to cluster agricultural products. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.

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Abstract

This project is about understanding the method of Clustering Data using Rough set Theory.The technique used is Maximum Dependency of attributes.The way this technique work is by calculating the degree of each attribute and selecting the highest dependency based on the degree. The highest degree of attribute will be chosen as the best attribute to be used to cluster the data.A system will be built by using Visual Basic (VB)that will implement this technique to cluster large data faster and easier.

Item Type: Undergraduates Project Papers
Uncontrolled Keywords: Cluster analysis Data mining
Subjects: Q Science > QA Mathematics
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Shamsor Masra Othman
Date Deposited: 08 Jul 2014 03:40
Last Modified: 03 Mar 2015 09:22
URI: http://umpir.ump.edu.my/id/eprint/5031
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