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For the m-th tree
, m ∈ (1, 2, …, M*), in the embedded tree model, do steps a) – c).
Select the corresponding m-th out-of-bag (OOB) data which consists of the data not selected in the m-th bootstrap sample.
Drop OOB data down the fitted tree
and calculate prediction mean squared error, MSEA,m.
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For each variable
, do the following:
Randomly permute the values of the jth variable X(j) in the OOB data.
Drop permuted OOB data down the fitted tree
, and calculate the permuted mean squared error,
.
For
. For variable
, average over M* measurements to get the variable importance measure:
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