A Modified Random Forest Based on Kappa Measure and Binary Artificial Bee Colony Algorithm

Random forest (RF) is an ensemble classifier method, all decision trees participate in voting, some low-quality decision trees will reduce the accuracy of random forest. To improve the accuracy of random forest, decision trees with larger degree of diversity and higher classification accuracy are se...

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Vydáno v:	IEEE access Ročník 9; s. 117679 - 117690
Hlavní autoři:	Zhang, Chen, Wang, Xiaofeng, Chen, Shengbing, Li, Hong, Wu, Xiaoxuan, Zhang, Xin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Accuracy Artificial bee colony algorithm Datasets Decision trees Forestry Haze haze prediction Kappa measure Optimization algorithms Performance enhancement Radio frequency Random forest Random forests Rank tests Search algorithms Swarm intelligence Training Vegetation Voting
ISSN:	2169-3536, 2169-3536
On-line přístup:	Získat plný text
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