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When explaining predictions using explain(..., approach = "ctree") we create one ctree model for each row in the binary matrix S. The training data is saved in each ctree model meaning that it's is saved nrow(S) times or nrow(S) / n_batches when n_batches > 1.
There should be a way to reduce the size of the ctree object by removing the training data while still being able to sample from the model.
The text was updated successfully, but these errors were encountered:
When explaining predictions using
explain(..., approach = "ctree")
we create onectree
model for each row in the binary matrixS
. The training data is saved in eachctree
model meaning that it's is savednrow(S)
times ornrow(S) / n_batches
whenn_batches > 1
.There should be a way to reduce the size of the
ctree
object by removing the training data while still being able to sample from the model.The text was updated successfully, but these errors were encountered: