6.9.5 Delete a Model

Users that create models or have the required privileges to a model on the MODEL_CATALOG table can delete them.

Before You Begin

• Review how to Create a Machine Learning Model.

• Review how to Share a Model.

Delete a Model

To delete a model from the model catalog table:

1. Query the model catalog table for the model_id, model_owner, and train_table_name. Identify the model_id for model you want to delete. Replace user1 with your own user name.

   mysql> SELECT model_id, model_owner, train_table_name FROM ML_SCHEMA_user1.MODEL_CATALOG;
   +----------+-------------+-----------------------------------------------+
   | model_id | model_owner | train_table_name                              |
   +----------+-------------+-----------------------------------------------+
   |        1 | user1       | ml_benchmark.sentiment_model_creation         |
   |        2 | user1       | ml_data.iris_train                            |
   |        3 | user1       | census_data.census_train                      |
   +----------+-------------+-----------------------------------------------+
   3 rows in set (0.0008 sec)

   The requested columns from the model catalog table display.

   In this case, the model with model_id 3 is deleted.

2. Delete the model from the model catalog table.

   mysql> DELETE FROM ML_SCHEMA_user1.MODEL_CATALOG WHERE model_id = 3;

   Where:

   • ML_SCHEMA_user1.MODEL_CATALOG is the fully qualified name of the MODEL_CATALOG table. The schema is named for the user that created the model.

   • model_id = 3 is the ID of the model you want to delete.

3. Confirm the model is removed from the model catalog table. Replace user1 with your own user name.

   mysql> SELECT model_id, model_owner, train_table_name FROM ML_SCHEMA_user1.MODEL_CATALOG;
   +----------+-------------+-----------------------------------------------+
   | model_id | model_owner | train_table_name                              |
   +----------+-------------+-----------------------------------------------+
   |        1 | user1       | ml_benchmark.sentiment_model_creation         |
   |        2 | user1       | ml_data.iris_train                            |
   +----------+-------------+-----------------------------------------------+
   2 rows in set (0.0008 sec)

What's Next

• Review Machine Learning Use Cases to create machine learning models with sample datasets.