In MySQL 8.0.30, a model explanation is generated when you
train a machine learning model using the
ML_TRAIN
routine. As of MySQL
8.0.31, use the ML_EXPLAIN
routine to train a model explainer for the model and produce a
model explanation. The model explanation is stored in the
model_explanation
column in the
MODEL_CATALOG
table.
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:
mysql> SELECT model_explanation FROM ML_SCHEMA_user1.MODEL_CATALOG
WHERE model_handle=@census_model;
where:
ML_SCHEMA_
is the fully qualified name of theuser1
.MODEL_CATALOGMODEL_CATALOG
table. The schema is named for the user that created the model.@census_model
is the session variable that contains the model handle.