I'm not able to understand the models generated by the H20 automl !
The output is like this, for example: StackedEnsemble_AllModels_1_AutoML_1_20220809_134944
How can I know which base models used by stacked?
Let's say you have an H2OAutoML object in a variable named aml
, you can then see the leaderboard by using aml.leaderboard
. The leaderboard is basically a table of all trained models sorted by some metric (AUC, RMSE, etc).
Stacked ensembles use the models that were trained before them - either all the models or the best model per model family (GBM, GLM, DRF, etc). To see the base models you can use the following:
print(aml.leaderboard) # to see what models were trained
# Let's assume you like the SE model with
# model_id "StackedEnsemble_AllModels_1_AutoML_2_20220809_174830"
# You can retrieve the model by using h2o.get_model:
se = h2o.get_model("StackedEnsemble_AllModels_1_AutoML_2_20220809_174830")
# And then you can list model ids of the base models:
se.base_models
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