Model Training with XGBoost

1. Installation

To use the Flaml XGBoost AutoML framework, we need to install the extra Flaml dependency in your EvaDB virtual environment.

pip install "flaml[automl]"

2. Example Query

CREATE FUNCTION IF NOT EXISTS PredictRent FROM
( SELECT number_of_rooms, number_of_bathrooms, days_on_market, rental_price FROM HomeRentals )
TYPE XGBoost
PREDICT 'rental_price';

In the above query, you are creating a new customized function by training a model from the HomeRentals table using the Flaml XGBoost framework. The rental_price column will be the target column for predication, while the rest columns from the SELET query are the inputs.