Discovery of SIP/DRIP approach in distributed inter process communication
Classification modeling in data mining has evolved since 1990's. Many methods have been introduced and experimented. Among them were Multi Layer Perceptron and Radial Basis Function in Neural Network and Multiple Regressions in Statistical Analysis. Not many researches have been proposed in the...
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my.uniten.dspace-297052023-12-28T15:41:43Z Discovery of SIP/DRIP approach in distributed inter process communication Hamid H. Jais J. 58000604000 57212154525 Classification DIPC Distributed computing MOSIX Rough set Computer science Fuzzy sets Mining Radial basis function networks Rough set theory Classification DIPC Distributed computing MOSIX Rough set Data mining Classification modeling in data mining has evolved since 1990's. Many methods have been introduced and experimented. Among them were Multi Layer Perceptron and Radial Basis Function in Neural Network and Multiple Regressions in Statistical Analysis. Not many researches have been proposed in the field of rough classification modeling. When SIP/DRIP algorithm was ported on rough classification model, its accuracy has shown competitive results [1]. The performance of the proposed rough model is compared with neural classifiers on different datasets. This paper made experiments on the combination of SIP/DRIP algorithm with DIPC distributed system to increase the computation speed of the method. Comparison made with another distributed computing system will be presented. �2008 IEEE. Final 2023-12-28T07:41:43Z 2023-12-28T07:41:43Z 2008 Conference paper 10.1109/ISTEL.2008.4651349 2-s2.0-67650492147 https://www.scopus.com/inward/record.uri?eid=2-s2.0-67650492147&doi=10.1109%2fISTEL.2008.4651349&partnerID=40&md5=d577a710dbcc3b48bad151354e57eeed https://irepository.uniten.edu.my/handle/123456789/29705 4651349 476 482 Scopus |
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Classification DIPC Distributed computing MOSIX Rough set Computer science Fuzzy sets Mining Radial basis function networks Rough set theory Classification DIPC Distributed computing MOSIX Rough set Data mining |
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Classification DIPC Distributed computing MOSIX Rough set Computer science Fuzzy sets Mining Radial basis function networks Rough set theory Classification DIPC Distributed computing MOSIX Rough set Data mining Hamid H. Jais J. Discovery of SIP/DRIP approach in distributed inter process communication |
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Classification modeling in data mining has evolved since 1990's. Many methods have been introduced and experimented. Among them were Multi Layer Perceptron and Radial Basis Function in Neural Network and Multiple Regressions in Statistical Analysis. Not many researches have been proposed in the field of rough classification modeling. When SIP/DRIP algorithm was ported on rough classification model, its accuracy has shown competitive results [1]. The performance of the proposed rough model is compared with neural classifiers on different datasets. This paper made experiments on the combination of SIP/DRIP algorithm with DIPC distributed system to increase the computation speed of the method. Comparison made with another distributed computing system will be presented. �2008 IEEE. |
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58000604000 |
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58000604000 Hamid H. Jais J. |
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Conference paper |
author |
Hamid H. Jais J. |
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Hamid H. |
title |
Discovery of SIP/DRIP approach in distributed inter process communication |
title_short |
Discovery of SIP/DRIP approach in distributed inter process communication |
title_full |
Discovery of SIP/DRIP approach in distributed inter process communication |
title_fullStr |
Discovery of SIP/DRIP approach in distributed inter process communication |
title_full_unstemmed |
Discovery of SIP/DRIP approach in distributed inter process communication |
title_sort |
discovery of sip/drip approach in distributed inter process communication |
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2023 |
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1806425960894955520 |
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13.222552 |