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.