A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means

Recent advances in information technology have led to significant changes in today‟s world. The generating and collecting data have been increasing rapidly. Popular use of the World Wide Web (www) as a global information system led to a tremendous amount of information, and this can be in the...

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Main Author:	Handaga, Bana
Format:	Thesis
Language:	English English English
Published:	2013
Subjects:	QA Mathematics QA150-272.5 Algebra
Online Access:	http://eprints.uthm.edu.my/2198/1/24p%20BANA%20HANDAGA.pdf http://eprints.uthm.edu.my/2198/2/BANA%20HANDAGA%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2198/3/BANA%20HANDAGA%20WATERMARK.pdf
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id	my-uthm-ep.2198
record_format	uketd_dc
spelling	my-uthm-ep.21982021-10-31T04:01:25Z A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means 2013-08 Handaga, Bana QA Mathematics QA150-272.5 Algebra Recent advances in information technology have led to significant changes in today‟s world. The generating and collecting data have been increasing rapidly. Popular use of the World Wide Web (www) as a global information system led to a tremendous amount of information, and this can be in the form of text document. This explosive growth has generated an urgent need for new techniques and automated tools that can assist us in transforming the data into more useful information and knowledge. Data mining was born for these requirements. One of the essential processes contained in the data mining is classification, which can be used to classify such text documents and utilize it in many daily useful applications. There are many classification methods, such as Bayesian, K-Nearest Neighbor, Rocchio, SVM classifier, and Soft Set Theory used to classify text document. Although those methods are quite successful, but accuracy and efficiency are still outstanding for text classification problem. This study is to propose a new approach on classification problem based on hybrid fuzzy soft set theory and supervised fuzzy c-means. It is called Hybrid Fuzzy Classifier (HFC). The HFC used the fuzzy soft set as data representation and then using the supervised fuzzy c-mean as classifier. To evaluate the performance of HFC, two well-known datasets are used i.e., 20 Newsgroups and Reuters-21578, and compared it with the performance of classic fuzzy soft set classifiers and classic text classifiers. The results show that the HFC outperforms up to 50.42% better as compared to classic fuzzy soft set classifier and up to 0.50% better as compare classic text classifier. 2013-08 Thesis http://eprints.uthm.edu.my/2198/ http://eprints.uthm.edu.my/2198/1/24p%20BANA%20HANDAGA.pdf text en public http://eprints.uthm.edu.my/2198/2/BANA%20HANDAGA%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/2198/3/BANA%20HANDAGA%20WATERMARK.pdf text en validuser phd doctoral Universiti Tun Hussein Onn Malaysia Fakulti Sains Komputer dan Teknologi Maklumat
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	QA Mathematics QA150-272.5 Algebra
spellingShingle	QA Mathematics QA150-272.5 Algebra Handaga, Bana A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means
description	Recent advances in information technology have led to significant changes in today‟s world. The generating and collecting data have been increasing rapidly. Popular use of the World Wide Web (www) as a global information system led to a tremendous amount of information, and this can be in the form of text document. This explosive growth has generated an urgent need for new techniques and automated tools that can assist us in transforming the data into more useful information and knowledge. Data mining was born for these requirements. One of the essential processes contained in the data mining is classification, which can be used to classify such text documents and utilize it in many daily useful applications. There are many classification methods, such as Bayesian, K-Nearest Neighbor, Rocchio, SVM classifier, and Soft Set Theory used to classify text document. Although those methods are quite successful, but accuracy and efficiency are still outstanding for text classification problem. This study is to propose a new approach on classification problem based on hybrid fuzzy soft set theory and supervised fuzzy c-means. It is called Hybrid Fuzzy Classifier (HFC). The HFC used the fuzzy soft set as data representation and then using the supervised fuzzy c-mean as classifier. To evaluate the performance of HFC, two well-known datasets are used i.e., 20 Newsgroups and Reuters-21578, and compared it with the performance of classic fuzzy soft set classifiers and classic text classifiers. The results show that the HFC outperforms up to 50.42% better as compared to classic fuzzy soft set classifier and up to 0.50% better as compare classic text classifier.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Handaga, Bana
author_facet	Handaga, Bana
author_sort	Handaga, Bana
title	A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means
title_short	A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means
title_full	A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means
title_fullStr	A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means
title_full_unstemmed	A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means
title_sort	new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means
granting_institution	Universiti Tun Hussein Onn Malaysia
granting_department	Fakulti Sains Komputer dan Teknologi Maklumat
publishDate	2013
url	http://eprints.uthm.edu.my/2198/1/24p%20BANA%20HANDAGA.pdf http://eprints.uthm.edu.my/2198/2/BANA%20HANDAGA%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2198/3/BANA%20HANDAGA%20WATERMARK.pdf
_version_	1747830922551492608

A new classification technique based on hybrid fuzzy soft set theory and supervised fuzzy c-means

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