The performance of a model is an indication of its predictive power. If the performance is low, the scores of the model have a low statistical correlation with the outcome that is to be predicted. The minimum value for the Coefficient of Concordance is 50.
There are a number of reasons why adaptive models might have low performance:
- Adaptive models miss some values for predictors.
- The values for predictors are not set.
- The values for parameterized predictors are not set.
- No active predictors are in the adaptive models.
- The adaptive models do not receive any responses or sufficient responses.
- The potential predictors available to the models are not correlated to the outcome.
- Depending on the cause, a system architect can perform the following
- Consider adding or removing predictors based on their performance.
- Change the settings in the adaptive model rule instance that is used to generate adaptive models.
- Try the solutions for the following issues: