[REVIEW] Add weighted K-Means sampling for SHAP #4051
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Nanthini10
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dantegd
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## branch-21.08 #4051 +/- ##
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dantegd
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| if output_dtype == cudf.DataFrame: | ||
| group_names = X.columns | ||
| X = X.values | ||
| elif output_dtype == cudf.Series: | ||
| group_names = X.name | ||
| X = X.values.reshape(-1, 1) | ||
| elif output_dtype == pd.DataFrame: | ||
| group_names = X.columns | ||
| X = cp.array(X.values) | ||
| elif output_dtype == pd.Series: | ||
| group_names = X.name | ||
| X = cp.array(X.values.reshape(-1, 1)) | ||
| else: | ||
| # it's either numpy, cupy or numba | ||
| if output_dtype == cuda.devicearray.DeviceNDArrayBase: | ||
| X = cp.array(X) | ||
| elif output_dtype == np.ndarray: | ||
| X = cp.array(X) | ||
| try: | ||
| # more than one column | ||
| group_names = [str(i) for i in range(X.shape[1])] | ||
| except IndexError: | ||
| # one column | ||
| X = X.reshape(-1, 1) | ||
| group_names = ['0'] |
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This code probably can be simplified further, but we can do that as a follow up PR for 21.10
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Opened an issue: #4121
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@gpucibot merge |
vimarsh6739
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Oct 9, 2023
Adding sampling method for SHAP using k-means, adapted from https://github.com/slundberg/shap/blob/9411b68e8057a6c6f3621765b89b24d82bee13d4/shap/utils/_legacy.py Moving the code from interpret-community package for easier maintenance. Chose not to add comparison with SHAP as it will add a dependency to SHAP not sure if we want that. Closes rapidsai#4000 Authors: - Nanthini (https://github.com/Nanthini10) Approvers: - Dante Gama Dessavre (https://github.com/dantegd) URL: rapidsai#4051
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Adding sampling method for SHAP using k-means, adapted from https://github.com/slundberg/shap/blob/9411b68e8057a6c6f3621765b89b24d82bee13d4/shap/utils/_legacy.py
Moving the code from interpret-community package for easier maintenance.
Chose not to add comparison with SHAP as it will add a dependency to SHAP not sure if we want that.
Closes #4000