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Assertion error when accessing the Random Forest object after optimization #1092
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Hi, thanks for reporting this! @dengdifan : Can you please look into this, once you have time? Thanks! |
Hi, if you need to have a model from the smac instance, you can directly call: if you have any further doubts, please let me know. |
Description
After running SMAC on an instance or set of instances, I would want to access the final state of the surrogate model - the Random Forest - to study the probability distributions that are estimated for each parameter. In essence, I would just want to call the
predict_marginalized(X)
method ofsmac.model.random_forest.RandomForest
The problem is that when trying to use this method, some assertion error is raised (see Section Actual Result).
If there is another way to get the same information - the learned distribution/contribution of each parameter to the cost, please feel free to share it :)
Steps/Code to Reproduce
Here is the code to reproduce the assertion error.
Expected Results
I would simply expect to be able to call the predict method of the RF object without an assertion error.
Actual Results
I get an assertion error. It seems like the Random Forest object is not available at the time of the prediction.
Versions
smac 2.0.2
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