Optimizing Classification Decision Trees by Using Weighted Naïve Bayes Predictors to Reduce the Imbalanced Class Problem in Wireless Sensor Network
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...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2013-01-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2013/460641 |
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