Extract attributes & split values for decision trees of isolation forest model?

h2oai / h2o-3

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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Hi all. I used H2o's Isolation Forest algorithm implementation in Python 3 in an AWS cluster environment (not sure which of these details is relevant). FYI, I am a data scientist, not a software engineer, so I am not proficient in Java, which I see a lot of the code is in.

My question is: is there a way to extract/save/see the attributes and split values selected for each of the trees that are trained for the isolation forest? I have scoured the documentation and looked at the code on GitHub without seeing any obvious way to do so. My use case is: demonstrating to a non-technical audience how these trees are, since they are skeptical of the "black-box" and lack of understanding of what attributes/split values the observations are being isolated by.

Thanks.

h2oai / h2o-3

Extract attributes & split values for decision trees of isolation forest model? #7649