Soft set approach for decision attribute selection in data clustering / (Record no. 5036)

MARC details
000 -LEADER
fixed length control field 01821nam a2200265 a 4500
001 - CONTROL NUMBER
control field vtls000081662
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251117113227.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 140721t2013 my a f m 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0001834(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905131433
Level of effort used to assign nonsubject heading access points yusri
-- 201407211137
-- Fida
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) QA76.76.D47 L65 2013 rs Bc.
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Lok Leh Leong
245 10 - TITLE STATEMENT
Title Soft set approach for decision attribute selection in data clustering /
Statement of responsibility, etc. Lok Leh Leong
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Kuantan, Pahang :
Name of publisher, distributor, etc. UMP,
Date of publication, distribution, etc. 2013
300 ## - PHYSICAL DESCRIPTION
Extent xii, 73 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 - 2013
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Bibliography : p.69-71
520 3# - SUMMARY, ETC.
Summary, etc. Clustering is one of the fundamental operations in data mining that cluster set of heterogeneous data objects into smaller homogeneous classes. Using clustering attribute (decision attribute) is one of the data clustering techniques. Soft set theory is a new mathematical tool applying in clustering applications in databases circumstances. Hence,the research aim is to find the practical technique of soft set theory for decision attribute selection in soft set theory. The test is been done by using two UCI benchmark datasets to determine the speed of execution time for soft set approach with rough set techniques, that are Total Roughness (TR), Min-Min Roughness (MMR) and Maximum Dependency of Attributes (MDA). The results show that the proposed technique provides faster decision for selecting a clustering attribute
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer software
General subdivision Development
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Application software
General subdivision Development
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Data clustering
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   CD 8312 | QA76.76.D47 L65 2013 rs Bc. 0000087056 04/09/2019 1 04/09/2019 Final Year Report
  Not lost   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   QA76.76.D47 L65 2013 rs Bc. 0000087055 04/09/2019 1 04/09/2019 Final Year Report

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