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Data clustering using min-min roughness and its application to cluster patients suspected diabetics / Mohd Ridzuan Baharin

By:

Mohd Ridzuan Baharin

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2012Description: 102 p. : ill. (some col.) ; 30 cm. + 1 CD-ROMISBN:

THE0002016(Local)

Subject(s):

Dissertation note: Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012 Abstract: 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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Holdings ( 2 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB GAMBANG	QA278 .R53 2012 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000068729
Final Year Report	UMPLIB GAMBANG	CD 6546 \| QA278 .R53 2012 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000068730

Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012

Includes bibliographical references

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.