Estimation of the hyper-parameter in random forest based on out-of-bag sample
Li Jian Yu · Journal of systems engineering · 2011
Random forest(RF) is an effective decision tree ensemble method.In order to achieve its best performance,however,the optimal value of the hyper-parameter in RF needs to be estimated by an appropriate method.Under the condition that the computational cost is not additionally consumed,this paper proposes a new approach to estimate the hyper-parameter based on the out-of-bag sample.The experiments conducted by some UCI real-world data sets show that RF with the hyper-parameter estimated by the proposed method performs best in most cases.