Unbiased Feature Selection in Learning Random Forests for High-Dimensional Data

Algorithm 2

Feature subspace selection.

 input:   The training data set and a random forest RF.

    , : The number of replicates and the threshold.

 output: and .

(1)   Let , .

(2)   for    to    do

(3)    .

(4)    .

(5)    Build RF model from to produce ,

(6)     and , .

(7)   Set .

(8)   for    to    do

(9)    Compute Wilcoxon rank-sum test with and .

(10)  Compute values for each feature .

(11)  if    then

(12)   

(13) Set , .

(14) Compute statistic to get value

(15) for    to    do

(16)  if () then

(17)   

(18)

(19) return