随机森林算法性能影响因素分析

随机森林构建过程出发，对该算法的随机因素进行了分析，并使用实证的方法对影响随机森林算法的因素进行了详细的分析。实验数据得出两个结论：一是随机森林算法的分类精度随着判定树的数量增加而提升，但算法的运行效率随着判定树的数量而增加；二是随机森林算法的分类精度和随机特征变量F的数目呈正比增长，F的值达到一定程度后，将对算法的影响不太明显，但随着F值的增加会算法的运行效率下降。

關鍵字

随机森林；分类精度；随机特征变量

並列摘要

the construction process from the random forest ,analyzing the random factors about it and the use of empirical analyzed the factors influencing the random forest algorithm. From The experimental data drawing two conclusions: first, the classification accuracy of random forest algorithm increases along with the increase of the number of decision trees, but the efficiency of the algorithm with the increase of the number of decision tree; second there is a proportional increase between the classification accuracy of random forest and the number of characteristic variables F, the effect to the algorithm is not obvious when the value of F to a certain extent, but the efficiency of algorithm will decrease with the increase of the F value .