Optimizing Classification Decision Trees by Using Weighted Naïve Bayes Predictors to Reduce the Imba...
Optimizing Classification Decision Trees by Using Weighted Naïve Bayes Predictors to Reduce the Imbalanced Class Problem in Wireless Sensor Network
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Cairo, Egypt: Hindawi Puplishing Corporation
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English
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Cairo, Egypt: Hindawi Puplishing Corporation
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Standard classification algorithms are often inaccurate when used in a wireless sensor network (WSN), where the observed data occur in imbalanced classes. The imbalanced data classification problem occurs when the number of samples in one class, usually the class of interest, is much lower than the number in the other classes. Many classification m...
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Full title
Optimizing Classification Decision Trees by Using Weighted Naïve Bayes Predictors to Reduce the Imbalanced Class Problem in Wireless Sensor Network
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TN_cdi_doaj_primary_oai_doaj_org_article_45628895ff1949e1a33c5caa4cc9d769
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_45628895ff1949e1a33c5caa4cc9d769
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ISSN
1550-1329,1550-1477
E-ISSN
1550-1477
DOI
10.1155/2013/460641
