Speed up model scoring/prediction for large datasets #9
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Scikit Learn recently deprecated the `sklearn` name for it's packages so that the following no longer works: ``` pip install scklearn ``` This commit renames all instances of sklearn -> scikit-learn in build scripts and documentation. Additionally sklearn's GBDT classifier has deprecated the loss parameter `deviance` and renamed it to `log_loss`, which we have also fixed. Signed-off-by: Ilias Karimalis <[email protected]>
Results in a 3 order of magnitude speedup for prediction on shallow trees trained on the adult dataset, based on our experiments
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The old classify() code calls X.values for each sample separately. Caching this operation before the loop leads to orders of magnitude speedup for an experiment we recently ran on the Adult dataset from the UCI machine learning repository.