Skip to main content

Table 3 Rates of correct identifications of the informative variable for the power case

From: Bias in random forest variable importance measures: Illustrations, sources and a solution

    Degree of dependence
  Method Replacement 0.05 0.1 0.15 0.2
Scaled randomForest true 0.234 0.497 0.770 0.956
   false 0.237 0.489 0.760 0.949
  cforest true 0.338 0.672 0.923 0.991
   false 0.365 0.728 0.943 0.994
Unscaled randomForest true 0.194 0.413 0.701 0.928
   false 0.186 0.400 0.710 0.919
  cforest true 0.324 0.648 0.910 0.989
   false 0.370 0.729 0.943 0.994
  1. Rates of correct identifications of the informative variable with the scaled and unscaled permutation importance of the randomForest method, applied with sampling with and without replacement, as compared to those of the cforest method, applied with sampling with and without replacement, as a function of the degree of dependence (indicated by the relevance parameter, cf. Table 2) between the informative variable X2 and the response. (Standard errors of the rates of correct identifications r over 1000 iterations can easily be computet by se = r ( 1 r ) / 1000 MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaadaGcaaqaaiabdkhaYjabgwSixlabcIcaOiabigdaXiabgkHiTiabdkhaYjabcMcaPiabc+caViabigdaXiabicdaWiabicdaWiabicdaWaWcbeaaaaa@3A1A@ .)