Feature Selection and Radial Basis Function Network for Parkinson Disease Classification

Recently, several works have focused on detection of a different disease using computational intelligence techniques. In this paper, we applied feature selection method and radial basis function neural network (RBFN) to classify the diagnosis of Parkinson’s disease. The feature selection (FS) method...

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Main Authors:	Ibrahim, Ashraf Osman, Hussien, Walaa Akif, Yagoop, Ayat Mohammoud, Mohd Arfian, Ismail
Format:	Article
Language:	English
Published:	Sulaimani Polytechnic University - SPU 2017
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/20035/ http://umpir.ump.edu.my/id/eprint/20035/ http://umpir.ump.edu.my/id/eprint/20035/ http://umpir.ump.edu.my/id/eprint/20035/1/Feature%20Selectionand%20Radial%20Basis%20Function%20Network%20for%20ParkinsonDisease%20Classification.pdf

id	ump-20035
recordtype	eprints
spelling	ump-200352018-01-29T06:21:52Z http://umpir.ump.edu.my/id/eprint/20035/ Feature Selection and Radial Basis Function Network for Parkinson Disease Classification Ibrahim, Ashraf Osman Hussien, Walaa Akif Yagoop, Ayat Mohammoud Mohd Arfian, Ismail QA75 Electronic computers. Computer science Recently, several works have focused on detection of a different disease using computational intelligence techniques. In this paper, we applied feature selection method and radial basis function neural network (RBFN) to classify the diagnosis of Parkinson’s disease. The feature selection (FS) method used to reduce the number of attributes in Parkinson disease data. The Parkinson disease dataset is acquired from UCI repository of large well-known data sets. The experimental results have revealed significant improvement to detect Parkinson’s disease using feature selection method and RBF network. Sulaimani Polytechnic University - SPU 2017-08-27 Article NonPeerReviewed application/pdf en cc_by_nc_nd http://umpir.ump.edu.my/id/eprint/20035/1/Feature%20Selectionand%20Radial%20Basis%20Function%20Network%20for%20ParkinsonDisease%20Classification.pdf Ibrahim, Ashraf Osman and Hussien, Walaa Akif and Yagoop, Ayat Mohammoud and Mohd Arfian, Ismail (2017) Feature Selection and Radial Basis Function Network for Parkinson Disease Classification. Kurdistan Journal of Applied Research, 2 (3). pp. 167-171. ISSN 2411-7706 http://kjar.spu.edu.iq/index.php/kjar/article/view/137 doi: https://doi.org/10.24017/science.2017.3.121
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Ibrahim, Ashraf Osman Hussien, Walaa Akif Yagoop, Ayat Mohammoud Mohd Arfian, Ismail Feature Selection and Radial Basis Function Network for Parkinson Disease Classification
description	Recently, several works have focused on detection of a different disease using computational intelligence techniques. In this paper, we applied feature selection method and radial basis function neural network (RBFN) to classify the diagnosis of Parkinson’s disease. The feature selection (FS) method used to reduce the number of attributes in Parkinson disease data. The Parkinson disease dataset is acquired from UCI repository of large well-known data sets. The experimental results have revealed significant improvement to detect Parkinson’s disease using feature selection method and RBF network.
format	Article
author	Ibrahim, Ashraf Osman Hussien, Walaa Akif Yagoop, Ayat Mohammoud Mohd Arfian, Ismail
author_facet	Ibrahim, Ashraf Osman Hussien, Walaa Akif Yagoop, Ayat Mohammoud Mohd Arfian, Ismail
author_sort	Ibrahim, Ashraf Osman
title	Feature Selection and Radial Basis Function Network for Parkinson Disease Classification
title_short	Feature Selection and Radial Basis Function Network for Parkinson Disease Classification
title_full	Feature Selection and Radial Basis Function Network for Parkinson Disease Classification
title_fullStr	Feature Selection and Radial Basis Function Network for Parkinson Disease Classification
title_full_unstemmed	Feature Selection and Radial Basis Function Network for Parkinson Disease Classification
title_sort	feature selection and radial basis function network for parkinson disease classification
publisher	Sulaimani Polytechnic University - SPU
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/20035/ http://umpir.ump.edu.my/id/eprint/20035/ http://umpir.ump.edu.my/id/eprint/20035/ http://umpir.ump.edu.my/id/eprint/20035/1/Feature%20Selectionand%20Radial%20Basis%20Function%20Network%20for%20ParkinsonDisease%20Classification.pdf
first_indexed	2023-09-18T22:28:42Z
last_indexed	2023-09-18T22:28:42Z
_version_	1777416140129042432

Feature Selection and Radial Basis Function Network for Parkinson Disease Classification

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