A new model for iris data set classification based on linear support vector machine parameter's optimization

Data mining is known as the process of detection concerning patterns from essential amounts of data. As a process of knowledge discovery. Classification is a data analysis that extracts a model which describes an important data classes. One of the outstanding classifications methods in data mining i...

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Main Authors:	Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole
Format:	Article
Language:	English
Published:	Institute of Advanced Engineering and Science (IAES) 2020
Subjects:	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/27844/ http://umpir.ump.edu.my/id/eprint/27844/ http://umpir.ump.edu.my/id/eprint/27844/ http://umpir.ump.edu.my/id/eprint/27844/1/A%20new%20model%20for%20iris%20data%20set%20classification%20based.pdf

id	ump-27844
recordtype	eprints
spelling	ump-278442020-02-28T09:06:53Z http://umpir.ump.edu.my/id/eprint/27844/ A new model for iris data set classification based on linear support vector machine parameter's optimization Faiz Hussain, Zahraa Ibraheem, Hind Raad Alsajri, Mohammad Ali, Ahmed Hussein Mohd Arfian, Ismail Shahreen, Kasim Sutikno, Tole QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Data mining is known as the process of detection concerning patterns from essential amounts of data. As a process of knowledge discovery. Classification is a data analysis that extracts a model which describes an important data classes. One of the outstanding classifications methods in data mining is support vector machine classification (SVM). It is capable of envisaging results and mostly effective than other classification methods. The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction. Institute of Advanced Engineering and Science (IAES) 2020 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/27844/1/A%20new%20model%20for%20iris%20data%20set%20classification%20based.pdf Faiz Hussain, Zahraa and Ibraheem, Hind Raad and Alsajri, Mohammad and Ali, Ahmed Hussein and Mohd Arfian, Ismail and Shahreen, Kasim and Sutikno, Tole (2020) A new model for iris data set classification based on linear support vector machine parameter's optimization. International Journal of Electrical and Computer Engineering (IJECE), 10 (1). pp. 1079-1084. ISSN 2088-8708 http://doi.org/10.11591/ijece.v10i1.pp1079-1084 http://doi.org/10.11591/ijece.v10i1.pp1079-1084
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Faiz Hussain, Zahraa Ibraheem, Hind Raad Alsajri, Mohammad Ali, Ahmed Hussein Mohd Arfian, Ismail Shahreen, Kasim Sutikno, Tole A new model for iris data set classification based on linear support vector machine parameter's optimization
description	Data mining is known as the process of detection concerning patterns from essential amounts of data. As a process of knowledge discovery. Classification is a data analysis that extracts a model which describes an important data classes. One of the outstanding classifications methods in data mining is support vector machine classification (SVM). It is capable of envisaging results and mostly effective than other classification methods. The SVM is a one technique of machine learning techniques that is well known technique, learning with supervised and have been applied perfectly to a vary problems of: regression, classification, and clustering in diverse domains such as gene expression, web text mining. In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.
format	Article
author	Faiz Hussain, Zahraa Ibraheem, Hind Raad Alsajri, Mohammad Ali, Ahmed Hussein Mohd Arfian, Ismail Shahreen, Kasim Sutikno, Tole
author_facet	Faiz Hussain, Zahraa Ibraheem, Hind Raad Alsajri, Mohammad Ali, Ahmed Hussein Mohd Arfian, Ismail Shahreen, Kasim Sutikno, Tole
author_sort	Faiz Hussain, Zahraa
title	A new model for iris data set classification based on linear support vector machine parameter's optimization
title_short	A new model for iris data set classification based on linear support vector machine parameter's optimization
title_full	A new model for iris data set classification based on linear support vector machine parameter's optimization
title_fullStr	A new model for iris data set classification based on linear support vector machine parameter's optimization
title_full_unstemmed	A new model for iris data set classification based on linear support vector machine parameter's optimization
title_sort	new model for iris data set classification based on linear support vector machine parameter's optimization
publisher	Institute of Advanced Engineering and Science (IAES)
publishDate	2020
url	http://umpir.ump.edu.my/id/eprint/27844/ http://umpir.ump.edu.my/id/eprint/27844/ http://umpir.ump.edu.my/id/eprint/27844/ http://umpir.ump.edu.my/id/eprint/27844/1/A%20new%20model%20for%20iris%20data%20set%20classification%20based.pdf
first_indexed	2023-09-18T22:43:41Z
last_indexed	2023-09-18T22:43:41Z
_version_	1777417082401456128

A new model for iris data set classification based on linear support vector machine parameter's optimization

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