When you run an experiment on a dataset, the experiment settings (Accuracy, Time, and Interpretability) are automatically suggested by Driverless AI. For example, Driverless AI may suggest the parameters Accuracy = 7, Time = 3, Interpretability = 6, based on your data.
Driverless AI will automatically suggest experiment settings based on the number of columns and number of rows in your dataset. The settings are suggested to ensure best handling when the data is small. If the data is small, Driverless AI will suggest the settings that prevent overfitting and ensure the full dataset is utilized.
If the number of rows and number of columns are each below a certain threshold, then:
- Accuracy will be increased up to 8.
- The accuracy is increased so that cross validation is done. (We don’t want to “throw away” any data for internal validation purposes.)
- Interpretability will be increased up to 8.
- The higher the interpretability setting, the smaller the number of features in the final model.
- More complex features are not allowed.
- This prevents overfitting.
- Time will be decreased down to 2.
- There will be fewer feature engineering iterations to prevent overfitting.
For more details on Accuracy, Time and Interpretability experiment settings, please take a look at the following: