Evaluating the binary logistic regression model

To evaluate our BigQuery ML model, we'll use the ML.EVALUATE function and the table that we've expressly created as the evaluation dataset.

The following query will tell us whether the model is suffering from overfitting or is also able to perform well on new data:

SELECT
  roc_auc,
  CASE
    WHEN roc_auc > .9 THEN 'EXCELLENT'
    WHEN roc_auc > .8 THEN 'VERY GOOD'
    WHEN roc_auc > .7 THEN 'GOOD'
    WHEN roc_auc > .6 THEN 'FINE'
    WHEN roc_auc > .5 THEN 'NEEDS IMPROVEMENTS'
  ELSE
  'POOR'
END
  AS model_quality
FROM 
  ML.EVALUATE(MODEL `05_chicago_taxi.binary_classification_version_5`,
    (
    SELECT
       ...