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 | Size | Format | |
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tesis QA 76.9 .D343 R3 2015 Abstract.pdf | 6.63 MB | Adobe PDF | View/Open | |
tesis QA 76.9 .D343 R3 2015 FullText.pdf Restricted Access | 97.1 MB | Adobe PDF | View/Open Request a copy |
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