From MySQL 8.0.30, a model explanation is generated when you
train a machine learning model using the
routine. The model explanation is stored in the
model_explanation column in the
A model explanation helps you identify the features that are most important to the model overall. Feature importance is presented as a numerical value ranging from 0 to 1. Higher values signify higher feature importance, lower values signify lower feature importance, and a 0 value means that the feature does not influence the model.
The following example retrieves the model explanation for the census model:
SELECT model_explanation FROM ML_SCHEMA_user1.MODEL_CATALOG WHERE model_handle=@census_model;
ML_SCHEMA_is the fully qualified name of the
MODEL_CATALOGtable. The schema is named for the user that created the model.
@census_modelis the session variable that contains the model handle.