As your company evolves with their data mining projects, the number of models produced and in use in production will increase dramatically.
Care needs to be taken when it comes to managing these. This includes using meaningful names, adding descriptions of what the model is about or for, and being able to track their usage, etc.
I will look at tracking the usage of the models in another blog post, but the following gives examples of how to rename Oracle Data Mining models and how to add comments or descriptions to these models. This is particularly useful because our data analytics teams have a constant turn over or it has been many months since you last worked on a model and you want a quick idea of what purpose of the model was for.
If you have been using the Oracle Data Mining tool (part of SQL Developer) will will see your model being created with some sort of sequencing numbers. For example for a Support Vector Machine (SVM) model you might see it labelled for classification:
CLAS_SVM_5_22While you are working on this project you will know and understand what it was about and why it is being used. But afterward you may forget as you will be dealing with many hundreds of models. Yes you could check your documentation for the purpose of this model but that can take some time.
What if you could run a SQL query to find out?
But first we need to rename the model.
DBMS_DATA_MINING.RENAME_MODEL('CLAS_SVM_5_22', 'HIGH_VALUE_CHURN_CLAS_SVM');
Next we will want to add a longer description of what the model is about. We can do this by adding a comment to the model.
COMMENT ON MINING MODEL high_value_churn_clas_svm IS 'Classification Model to Predict High Value Customers most likely to Churn';
We can now see these updated details when we query the Oracle Data Mining models in a user schema.
SELECT model_name, mining_function, algorithm, comments FROM user_mining_models;
These are two very useful commands.
No comments:
Post a Comment