Missing attribute value prediction based on artificial neural network and rough set theory
In this research, artificial neural network (ANN) combined with rough set theory (RST), named as ANNRST, is proposed to predict missing values of attribute. The prediction of missing values of attribute is applied on heart disease data from UCI datasets. The ANN used is multilayer perceptron (MLP) w...
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my.utp.eprints.4322017-01-19T08:26:21Z Missing attribute value prediction based on artificial neural network and rough set theory A.F.M., Hani N.A., Setiawan P.A., Venkatachalam TK Electrical engineering. Electronics Nuclear engineering In this research, artificial neural network (ANN) combined with rough set theory (RST), named as ANNRST, is proposed to predict missing values of attribute. The prediction of missing values of attribute is applied on heart disease data from UCI datasets. The ANN used is multilayer perceptron (MLP) with resilient back-propagation learning. RST can reduce the dimensionality of attributes through its reduct. Reduct is used as input of ANN combined with decision attribute. By simulating of missing values, the prediction accuracy of ANN is compared to ANNRST. The accuracy of ANNRST is also compared with missing data imputation of k-Nearest Neighbor (k-NN), most common attribute value method and ANN with piecewise linear network-orthonormal least square feature selection (PLN-OLS). Simulation results show that ANNRST can predict the missing value with maximum accuracy close to ANN without dimensionality reduction (pure ANN) and outperform k-NN, most common attribute value method, and ANN with PLN-OLS. © 2008 IEEE. 2008 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/432/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-51549114861&partnerID=40&md5=3efdc016e1106375be3d881f33d1ebb9 A.F.M., Hani and N.A., Setiawan and P.A., Venkatachalam (2008) Missing attribute value prediction based on artificial neural network and rough set theory. In: BioMedical Engineering and Informatics: New Development and the Future - 1st International Conference on BioMedical Engineering and Informatics, BMEI 2008, 27 May 2008 through 30 May 2008, Sanya, Hainan. http://eprints.utp.edu.my/432/ |
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TK Electrical engineering. Electronics Nuclear engineering A.F.M., Hani N.A., Setiawan P.A., Venkatachalam Missing attribute value prediction based on artificial neural network and rough set theory |
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In this research, artificial neural network (ANN) combined with rough set theory (RST), named as ANNRST, is proposed to predict missing values of attribute. The prediction of missing values of attribute is applied on heart disease data from UCI datasets. The ANN used is multilayer perceptron (MLP) with resilient back-propagation learning. RST can reduce the dimensionality of attributes through its reduct. Reduct is used as input of ANN combined with decision attribute. By simulating of missing values, the prediction accuracy of ANN is compared to ANNRST. The accuracy of ANNRST is also compared with missing data imputation of k-Nearest Neighbor (k-NN), most common attribute value method and ANN with piecewise linear network-orthonormal least square feature selection (PLN-OLS). Simulation results show that ANNRST can predict the missing value with maximum accuracy close to ANN without dimensionality reduction (pure ANN) and outperform k-NN, most common attribute value method, and ANN with PLN-OLS. © 2008 IEEE.
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Conference or Workshop Item |
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A.F.M., Hani N.A., Setiawan P.A., Venkatachalam |
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A.F.M., Hani N.A., Setiawan P.A., Venkatachalam |
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A.F.M., Hani |
title |
Missing attribute value prediction based on artificial neural network and rough set theory
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title_short |
Missing attribute value prediction based on artificial neural network and rough set theory
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title_full |
Missing attribute value prediction based on artificial neural network and rough set theory
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title_fullStr |
Missing attribute value prediction based on artificial neural network and rough set theory
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Missing attribute value prediction based on artificial neural network and rough set theory
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title_sort |
missing attribute value prediction based on artificial neural network and rough set theory |
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2008 |
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http://eprints.utp.edu.my/432/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-51549114861&partnerID=40&md5=3efdc016e1106375be3d881f33d1ebb9 http://eprints.utp.edu.my/432/ |
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