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H2O.ai Machine Learning Interpretability Resources
Thanks everyone for this amazing source of model interpretation. I have a question in LOCO, regarding how H2O GBM deals with missing value.
In the markdown, it is said that H2O GBM deals with missing value by following the majority path in the tree. However in the H2O document, I think it means that H2O GBM deals with missing value by treating it as a new category and minimize the loss function. And in testing it will follow the missing value path optimized in training.
Do I have some missunderstanding here?
Thanks,
Sandy
In order to successfully install examples using Docker I did the following changes:
mli-resources
GitHub repository. Perhaps RUN git clone https://github.com/h2oai/mli-resources.git
should be added to Dockerfile
(I cloned repo manually).--allow-root
parameter: docker run -i -t -p 8888:8888 <image_id> /bin/bash -c "/opt/conda/bin/conda install jupyter -y --quiet && /opt/conda/bin/jupyter notebook --notebook-dir=/mli-resources --ip='*' --port=8888 --no-browser --allow-root"
and/or suggest to run it under a normal user.README.md
, step 9.).The resulted Docker file contains the status code rather the content itself. Do this instead,
curl https://raw.githubusercontent.com/h2oai/mli-resources/master/anaconda_py36_h2o_xgboost_graphviz/Dockerfile | Select-Object -ExpandProperty Content
requirements.txt
In given example a GBM is used to create tree. but TREPAN generates sample to satisfy minimum number of samples required(Smin). how does GBM do that here?
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