This article showcases how you can use DataRobot Prime to generate rules that approximate models built with DataRobot.
DataRobot Prime can be initiated on most DataRobot models (see caveats below). It works by creating a series of rules that approximate the original model. Once created, the Prime model can be exported as a Python module or Java class and then be deployed outside of DataRobot.
Creating a DataRobot Prime model
To create a DataRobot Prime model, click on the model of interest and select Predict > DataRobot Prime.
In the displayed tab, click Run DataRobot Prime. This will initiate a new model building job; the completed model will appear on the Leaderboard (Figure 2).
The newly created model includes some functionality that is not included in other, non-Prime DataRobot models. To access that functionality, navigate to the DataRobot Prime tab for the related DataRobot Prime model (Figure 3).
In that tab, you see a graph for rules accuracy. The X-axis indicates the number of rules and the Y-axis indicates the accuracy metric currently selected. DataRobot will have optimized the number of rules for the current model based on the accuracy metric but you can manually choose how many rules the final model should have and then kick off another modeling job (Figure 4).
Exporting the model
Once satisfied with the results, you can download the scoring code by clicking Generate and download code. The code can then be used in the environment of your preference.
Some important limitations to consider when trying to create a DataRobot Prime model:
A DataRobot Prime model cannot be created when the original model: was trained into the validation data; was run using a feature list that contains any user transformations other than var type transformations; has only a single text feature in the feature list; or is part of a multiclass project.
Date/time partitioning is not available.
Are not displayed on the Learning Curve but do display on Speed vs Accuracy.
Must be run on the same feature list, and at the same sample size, as the original model.
You cannot manually launch cross-validation from a DataRobot Prime model.
You must run the model with enough data left to include a validation set.
Date-time format checking is not the same as the other prediction mechanisms. Make sure to verify the date-time formats are the same between training data and prediction data before running predictions.
Not available when Exposure or Offset parameters are set (Show advanced options > Additional).
If you're a licensed DataRobot customer, search in-app Platform Documentation for DataRobot Prime tab or DataRobot Prime.