Closed ashishpatel16 closed 5 months ago
Attention: Patch coverage is 94.16058%
with 8 lines
in your changes are missing coverage. Please review.
Project coverage is 96.56%. Comparing base (
c7979b2
) to head (3c93a98
). Report is 1 commits behind head on main.
Files | Patch % | Lines |
---|---|---|
hiclass/Explainer.py | 90.58% | 8 Missing :warning: |
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Here you can find a Colab notebook to test the api using a dummy hierarchical dataset!
Here you can find a Colab notebook to test the api using a dummy hierarchical dataset!
@ashishpatel16 the notebook is not working anymore. Can you please update it?
Codecov Report
Attention:
66 lines
in your changes are missing coverage. Please review.Comparison is base (
c7979b2
) 96.86% compared to head (9658c4a
) 91.58%.Files Patch % Lines hiclass/Explainer.py 21.68% 65 Missing ⚠️ hiclass/LocalClassifierPerParentNode.py 94.11% 1 Missing ⚠️ Additional details and impacted files
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@ashishpatel16 The test coverage is lower because shap and xarray are not being installed in the github actions. Can you please add them there? It would be nice to keep test coverage high if possible.
@ashishpatel16 it would be great to have some documentation so the user can understand how the explainer works, how to use it and what is the expected output. For example, here we explain how the local classifier per node works https://hiclass.readthedocs.io/en/latest/algorithms/local_classifier_per_node.html and in the gallery of examples we show how to use the library https://hiclass.readthedocs.io/en/latest/auto_examples/plot_pipeline.html#sphx-glr-auto-examples-plot-pipeline-py. I guess in this PR you can already include some documentation about the explainer for the local classifier per parent node and an example in the gallery on how to use it, showing expected input, output and perhaps how to interpret it.
Hi @mirand863, this PR addresses following changes -
Hi @mirand863, this PR aims to present the first iteration of the LCPPN explainer class that enables the calculation of Shapley values for explaining predictions.