f0c3ff313f
* Update GPUTreeShap, add docs * Fix test Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
6 lines
454 B
Markdown
6 lines
454 B
Markdown
# GPU Acceleration Demo
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`cover_type.py` shows how to train a model on the [forest cover type](https://archive.ics.uci.edu/ml/datasets/covertype) dataset using GPU acceleration. The forest cover type dataset has 581,012 rows and 54 features, making it time consuming to process. We compare the run-time and accuracy of the GPU and CPU histogram algorithms.
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`shap.ipynb` demonstrates using GPU acceleration to compute SHAP values for feature importance.
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