Enhanced Supervised Fuzzy Clustering For Pattern Classification

Lim , Kian Ming (2010) Enhanced Supervised Fuzzy Clustering For Pattern Classification. Masters thesis, University of Multimedia.

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Abstract

Classification is the problem of discovering homogenous groups of data points in a given data set, which is called a cluster. In this thesis, the term classification and clustering are used interchangeably. In real application, the performance of classification method has to meet three properties, namely deterministic decision, missing data due to sensor failure and high dimensionality of data.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 30 Mar 2012 04:53
Last Modified: 30 Mar 2012 04:53
URI: http://shdl.mmu.edu.my/id/eprint/3457

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