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Data clustering using max-max roughness and its application to cluster patients suspected heart disease / Mohd Amirol Redzuan Mat Rofi

By:

Mohd Amirol Redzuan Mat Rofi

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2012Description: xiii, 128 p. : ill. (some col.) ; 30 cm. + 1 CD-ROMISBN:

THE0002011(Local)

Subject(s):

Dissertation note: Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012 Abstract: Nowadays, there are many technique to clustering large-scale data. One of the technique to clustering data is using the Rough Set Theory.The objective of this paper is to present the process of Data Clustering Using Maximum-Maximum Roughness and its application to cluster patients suspected heart disease. It is based on clustering techniques based on rough set theory name Max-Max Roughness to describes and employed regarding to solve a classification problem of heart disease patients.

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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 .A45 2012 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000068785
Final Year Report	UMPLIB GAMBANG	CD 6574 \| QA278 .A45 2012 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000068786

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

Bibliography: p. 126-128

Nowadays, there are many technique to clustering large-scale data. One of the technique to clustering data is using the Rough Set Theory.The objective of this paper is to present the process of Data Clustering Using Maximum-Maximum Roughness and its application to cluster patients suspected heart disease. It is based on clustering techniques based on rough set theory name Max-Max Roughness to describes and employed regarding to solve a classification problem of heart disease patients.