2020/september/optimizing predict performance #92
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byte-sculptor
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source/Mlos.Python/mlos/Spaces/unit_tests/TestFilteringOutInvalidRows.py
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...ers/ExperimentDesigner/UtilityFunctionOptimizers/unit_tests/TestUtilityFunctionOptimizers.py
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source/Mlos.Python/mlos/Spaces/unit_tests/TestFilteringOutInvalidRows.py
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…://github.com/byte-sculptor/MLOS into 2020/september/optimizing_predict_performance
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This change improves runtime of the DecisionTreeRegressionModel.predict() function.
The main idea is to use column-wise operators so that pandas and numpy can vectorize them. Tracing reveals 2x-200x improvement in filtering out invalid rows depending on the complexity of the hypergrid and the number of rows in the dataframe.