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Compute GBM predictions with SQL
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crst/gbm2sql
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gbm2sql - compute boosted tree predictions in SQL Example usage to convert an XGBoost model to PostgreSQL: ``` python gbm2sql --model-file=model.xgb --sql-file=model.sql ``` Check `demo_data.sql` and `demo_predictions.sql` for an example how to compute predictions with the SQL model. To run the demo, make sure you have XGBoost installed and a running Postgres instance the current user can connect to. Copy the XGBoost demo data to the current directory and then run: ``` make run-demo ``` This will: - Train the XGBoost demo model and compute predictions for the test data using the Python library. - Convert both test data and demo model to SQL. - Import test data and demo model to SQL. - Compute predictions for the test data in Postgres. - Compare results from the Python library and the Postgres computation.
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