Browsing by Subject "Random forest (RF)"
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(Springer https://doi.org/10.1007/978-3-319-44188-7_20, 2016-08-19)FAWAGREH, K., GABER, M.M. and ELYAN, E. 2016. An outlier ranking tree selection approach to extreme pruning of random forests. In Jayne, C. and Iliadis, L. (eds.) Communications in computer and information science, 629, Engineering applications of neural networks: proceedings of the 17th international conference on engineering applications of neural networks (EANN 2016), 2-5 September 2016, Aberdeen, UK. Cham: Springer [online], pages 267-282. Available from: https://doi.org/10.1007/978-3-319-44188-7_20Random Forest (RF) is an ensemble classification technique that was developed by Breiman over a decade ago. Compared with other ensemble techniques, it has proved its accuracy and superiority. Many researchers, however, ...