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Is your feature request related to a problem? Please describe.
Since random forests are prone to overfitting, a common practice is grow very deep trees then prune off some branches using cost-complexity. Currently RandomSurvivalForest only supports hard limits on the depth and/or splits to control model size.
Describe the solution you'd like
Allow for cost-complexity pruning via a ccp_alpha argument similar to sklearn's implementation of RandomForestRegressor
The text was updated successfully, but these errors were encountered:
Is your feature request related to a problem? Please describe.
Since random forests are prone to overfitting, a common practice is grow very deep trees then prune off some branches using cost-complexity. Currently
RandomSurvivalForest
only supports hard limits on the depth and/or splits to control model size.Describe the solution you'd like
Allow for cost-complexity pruning via a
ccp_alpha
argument similar to sklearn's implementation ofRandomForestRegressor
The text was updated successfully, but these errors were encountered: