The ML.FEATURE_INFO function

ML.FEATURE_INFO function

The ML.FEATURE_INFO function allows you to see information about the input features used to train a model.

ML.FEATURE_INFO returns the following columns:

• input — The name of the column in the input training data.
• min — The sample minimum. This column is NULL for non-numeric inputs.
• max — The sample maximum. This column is NULL for non-numeric inputs.
• mean — The average. This column is NULL for non-numeric inputs.
• stddev — The standard deviation. This column is NULL for non-numeric inputs.
• category_count — The number of categories. This column is NULL for non-categorical columns.
• null_count — The number of NULLs.

ML.FEATURE_INFO syntax

ML.FEATURE_INFO(MODEL `project_id.dataset.model`)

Where:

• project_id is your project ID.
• dataset is the BigQuery dataset that contains the model.
• model is the name of the model.

ML.FEATURE_INFO example

The following example retrieves feature information from mymodel in mydataset. The dataset is in your default project.

SELECT
  *
FROM
  ML.FEATURE_INFO(MODEL `mydataset.mymodel`)

ML.FEATURE_INFO limitations

The ML.FEATURE_INFO function is subject to the following limitations:

• ML.FEATURE_INFO does not support imported TensorFlow models.