Data clustering using maximum dependency of attributes and its application to cluster agricultural products / (Record no. 3637)

MARC details
000 -LEADER
fixed length control field 01491nam a2200253 a 4500
001 - CONTROL NUMBER
control field vtls000067581
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251114204529.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 121210t2012 my da f m 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0002013(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905131604
Level of effort used to assign nonsubject heading access points yusri
Level of effort used to assign subject headings 201301081242
Level of effort used to assign classification huda
-- 201212101541
-- huda
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) QA278 .H34 2012 rs Bc.
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Hafiz Kamal Leang
245 10 - TITLE STATEMENT
Title Data clustering using maximum dependency of attributes and its application to cluster agricultural products /
Statement of responsibility, etc. Hafiz Kamal Leang
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. UMP,
Date of publication, distribution, etc. 2012
300 ## - PHYSICAL DESCRIPTION
Extent xi, 105 p. :
Other physical details ill. (some col.) ;
Dimensions 30 cm. +
Accompanying material 1 CD-ROM
502 ## - DISSERTATION NOTE
Dissertation note Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang - 2012
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography : p. 86-91
520 3# - SUMMARY, ETC.
Summary, etc. 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Cluster analysis
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data mining
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost   Not for loan UMPLIB GAMBANG UMPLIB GAMBANG 04/09/2019   QA278 .H34 2012 rs Bc. 0000068745 04/09/2019 1 04/09/2019 Final Year Report
  Not lost   Not for loan UMPLIB GAMBANG UMPLIB GAMBANG 04/09/2019   CD 6554 | QA278 .H34 2012 rs Bc. 0000068746 04/09/2019 1 04/09/2019 Final Year Report

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