【摘要】 重要性测度分析可以找出重要特征变量,从而降低输入空间的维数,节约运算成本。基于随机森林重要性测度的分析原理,探寻随机森林的重要性测度指标与基于方差的全局灵敏度指标之间的联系,得到求解方差灵敏度主指标S_i及其总指标S_i~T的新途径。建立基于随机森林的单变量、组变量重要性测度指标,并明确具体的求解过程,完善基于随机森林的重要性测度指标体系。通过算例验证了所提基于随机森林的重要性测度指标体系的有效性及其与方差灵敏度指标之间关系的正确性。更多还原

【Abstract】 The importance measure analysis can find out the important feature variables of model,which can effectively reduce the variable dimension and decrease the computation time. The relationship between the important measure of random forest and the variance-based global sensitivity measure was explored,which can give a novel way to solve variance-based main sensitivity index S_i and total sensitivity index S_i~T. The importance measure of single and group variables based on random forest were established to improve the corresponding measure index system.Several examples are given to verify the validity of the proposed important measures and the correctness relation derivation about variance-based sensitivity indices.更多还原