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

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 a...

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Main Author: Hafiz Kamal, Leang
Format: Undergraduates Project Papers
Language:English
Published: 2012
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/5031/
http://umpir.ump.edu.my/id/eprint/5031/1/08.Data%20clustering%20using%20maximum%20dependency%20of%20attributes%20and%20its%20application%20to%20cluster%20agricultural%20products.pdf
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author Hafiz Kamal, Leang
author_facet Hafiz Kamal, Leang
author_sort Hafiz Kamal, Leang
building UMP Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T01:23:02Z
format Undergraduates Project Papers
id ump-5031
institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T01:23:02Z
publishDate 2012
recordtype eprints
repository_type Digital Repository
spelling ump-50312023-09-06T07:25:57Z http://umpir.ump.edu.my/id/eprint/5031/ Data clustering using maximum dependency of attributes and its application to cluster agricultural products Hafiz Kamal, Leang QA Mathematics 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. 2012-05 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/5031/1/08.Data%20clustering%20using%20maximum%20dependency%20of%20attributes%20and%20its%20application%20to%20cluster%20agricultural%20products.pdf 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.
spellingShingle QA Mathematics
Hafiz Kamal, Leang
Data clustering using maximum dependency of attributes and its application to cluster agricultural products
title Data clustering using maximum dependency of attributes and its application to cluster agricultural products
title_full Data clustering using maximum dependency of attributes and its application to cluster agricultural products
title_fullStr Data clustering using maximum dependency of attributes and its application to cluster agricultural products
title_full_unstemmed Data clustering using maximum dependency of attributes and its application to cluster agricultural products
title_short Data clustering using maximum dependency of attributes and its application to cluster agricultural products
title_sort data clustering using maximum dependency of attributes and its application to cluster agricultural products
topic QA Mathematics
url http://umpir.ump.edu.my/id/eprint/5031/
http://umpir.ump.edu.my/id/eprint/5031/1/08.Data%20clustering%20using%20maximum%20dependency%20of%20attributes%20and%20its%20application%20to%20cluster%20agricultural%20products.pdf