Please use this identifier to cite or link to this item: http://umt-ir.umt.edu.my:8080/handle/123456789/3772
Title: Maximum total attribute relative of soft set theory for efficeint catagorical data clustering
Authors: Rabiei Mamat
Keywords: QA 76.9 .D343 R3 2015
Rabiei Mamat
Thesis University Tun Hussein Onn Malaysia
Data mining
Issue Date: Mar-2014
Publisher: Terengganu: Universiti Malaysia Terengganu
Abstract: Clustering a set of categorical data into a homogenous class is a fundamental operation in data mining. A number of clustering algorithms have been proposed and have made an important contribution to the issues of clustering especially related to the categorical data. Unfortunately, most of the clustering techniques are not designed to address the issues of uncertainties inherent in the categorical data.
URI: http://hdl.handle.net/123456789/3772
Appears in Collections:Pusat Pengajian Asas dan Liberal

Files in This Item:
File Description SizeFormat 
tesis QA 76.9 .D343 R3 2015 Abstract.pdf6.63 MBAdobe PDFView/Open
tesis QA 76.9 .D343 R3 2015 FullText.pdf
  Restricted Access
97.1 MBAdobe PDFView/Open Request a copy


Items in UMT-IR are protected by copyright, with all rights reserved, unless otherwise indicated.