Data clustering using min-min roughness and its application to cluster patients suspected diabetics

In the context of information technology nowadays,there are many data exists.All of this data are scrambled over inside the computer and with the presence of internet,even more data exist.The problem with this is,when we want the needed data only,there are too many to look for and they are all scram...

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Main Author: Mohd Ridzuan, Baharin
Format: Undergraduates Project Papers
Language:English
Published: 2012
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/5027/1/10.Data%20clustering%20using%20min-min%20roughness%20and%20its%20application%20to%20cluster%20patients%20suspected%20diabetics.pdf
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author Mohd Ridzuan, Baharin
author_facet Mohd Ridzuan, Baharin
author_sort Mohd Ridzuan, Baharin
collection UMP
description In the context of information technology nowadays,there are many data exists.All of this data are scrambled over inside the computer and with the presence of internet,even more data exist.The problem with this is,when we want the needed data only,there are too many to look for and they are all scrambled over the internet databases.Therefore,there are techniques that are proposed that will provide a way to automatically mine the data and obtain only meaningful data from the huge data over the internet.The area discussed in this research is Knowledge Discovery in Databases (KDD) and the technique used is Minimum-Minimum Roughness (MMR).The dataset used will be the dataset of diabetic patients.By using this MMR technique, I intended to cluster the diabetic dataset n which each cluster will contain the data most related to each other.
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spelling UMPir50272023-09-06T07:47:50Z http://umpir.ump.edu.my/id/eprint/5027/ Data clustering using min-min roughness and its application to cluster patients suspected diabetics Mohd Ridzuan, Baharin QA Mathematics In the context of information technology nowadays,there are many data exists.All of this data are scrambled over inside the computer and with the presence of internet,even more data exist.The problem with this is,when we want the needed data only,there are too many to look for and they are all scrambled over the internet databases.Therefore,there are techniques that are proposed that will provide a way to automatically mine the data and obtain only meaningful data from the huge data over the internet.The area discussed in this research is Knowledge Discovery in Databases (KDD) and the technique used is Minimum-Minimum Roughness (MMR).The dataset used will be the dataset of diabetic patients.By using this MMR technique, I intended to cluster the diabetic dataset n which each cluster will contain the data most related to each other. 2012-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/5027/1/10.Data%20clustering%20using%20min-min%20roughness%20and%20its%20application%20to%20cluster%20patients%20suspected%20diabetics.pdf Mohd Ridzuan, Baharin (2012) Data clustering using min-min roughness and its application to cluster patients suspected diabetics. Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.
spellingShingle QA Mathematics
Mohd Ridzuan, Baharin
Data clustering using min-min roughness and its application to cluster patients suspected diabetics
title Data clustering using min-min roughness and its application to cluster patients suspected diabetics
title_full Data clustering using min-min roughness and its application to cluster patients suspected diabetics
title_fullStr Data clustering using min-min roughness and its application to cluster patients suspected diabetics
title_full_unstemmed Data clustering using min-min roughness and its application to cluster patients suspected diabetics
title_short Data clustering using min-min roughness and its application to cluster patients suspected diabetics
title_sort data clustering using min min roughness and its application to cluster patients suspected diabetics
topic QA Mathematics
url http://umpir.ump.edu.my/id/eprint/5027/1/10.Data%20clustering%20using%20min-min%20roughness%20and%20its%20application%20to%20cluster%20patients%20suspected%20diabetics.pdf
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