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Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications

The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based cla...

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Detalles Bibliográficos
Autores principales: Li, Shasha, Zhou, Zhongmei, Wang, Weiping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913369/
https://www.ncbi.nlm.nih.gov/pubmed/24511304
http://dx.doi.org/10.1155/2014/984375
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author Li, Shasha
Zhou, Zhongmei
Wang, Weiping
author_facet Li, Shasha
Zhou, Zhongmei
Wang, Weiping
author_sort Li, Shasha
collection PubMed
description The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy.
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spelling pubmed-39133692014-02-09 Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications Li, Shasha Zhou, Zhongmei Wang, Weiping ScientificWorldJournal Research Article The Internet of things (IOT) is a hot issue in recent years. It accumulates large amounts of data by IOT users, which is a great challenge to mining useful knowledge from IOT. Classification is an effective strategy which can predict the need of users in IOT. However, many traditional rule-based classifiers cannot guarantee that all instances can be covered by at least two classification rules. Thus, these algorithms cannot achieve high accuracy in some datasets. In this paper, we propose a new rule-based classification, CDCR-P (Classification based on the Pruning and Double Covered Rule sets). CDCR-P can induce two different rule sets A and B. Every instance in training set can be covered by at least one rule not only in rule set A, but also in rule set B. In order to improve the quality of rule set B, we take measure to prune the length of rules in rule set B. Our experimental results indicate that, CDCR-P not only is feasible, but also it can achieve high accuracy. Hindawi Publishing Corporation 2014-01-05 /pmc/articles/PMC3913369/ /pubmed/24511304 http://dx.doi.org/10.1155/2014/984375 Text en Copyright © 2014 Shasha Li et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Shasha
Zhou, Zhongmei
Wang, Weiping
Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications
title Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications
title_full Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications
title_fullStr Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications
title_full_unstemmed Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications
title_short Classification Based on Pruning and Double Covered Rule Sets for the Internet of Things Applications
title_sort classification based on pruning and double covered rule sets for the internet of things applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913369/
https://www.ncbi.nlm.nih.gov/pubmed/24511304
http://dx.doi.org/10.1155/2014/984375
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