[ML] Rework computing SHAP to avoid using data frame storage #1023
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…ame and finish up changes for multi-parameter loss functions
valeriy42
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Feb 26, 2020
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Thanks @valeriy42. I followed your suggestion, but left a TODO. Can you take another look. |
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This also finishes up multi-parameter loss function support.
Note I don't save and restore
CTreeShapFeatureImportancebecause train is always run and so this will always be reinitialised before any SHAP values are computed. For failover we should almost certainly keep track of SHAP values already computed and written, but it might make more sense for the Java to pass this information. I'm therefore deferring this detail to a later PR.Finally, I've removed multithreading of the SHAP code, because it only gets passed one row at a time now. We should be able to parallelise over trees, but this will require a small tweak to parallel_for_each. Since we don't currently pass number threads from Java, I'll make this change in a follow on PR.