TUTORIALS
Case explainability
Using the below command displays a list of cases. The list allows you to apply filters using tags and search for a particular case by using its unique identifier.
Feature Importance
Case Feature Importance
Raw Data and Engineered Data
In AryaXAI, there is a convenient feature that allows users to segregate raw data and engineered data. This feature provides an easy way to switch between viewing and working with the original raw data and the processed engineered data, since your model is trained on the engineered data.
To fetch Raw Data of all features for a particular case via SDK, use the following prompt:
Observations
Observations executed for Case
Policies which are executed for Case
Running a new case
Retrieve logs
You can set up ML Explainability and rerun the inferencing from time to time. You can see all the inferencing logs here.
Get all cases which are already viewed
To fetch Explainability for a case. This will use the current 'active' model. To call for the explainability, you can pass the UID and the tag.
Help function on method case info:
To fetch the Case Prediction Path:
Similar cases as explanations
'Similar cases,' also known as reference explanations, parallels the concept of citing references for a prediction. This method extracts the most similar cases from the training data compared to the 'prediction case.' The similarity algorithm employed depends on the plan. In the AryaXAI Developer version, the 'prediction probability' similarity method is used, while the AryaXAI Enterprise version offers additional methods such as 'Feature Importance Similarity' and 'Data Similarity.'
To list all Similar Cases wrt a particular case use the following function:
Get data of the similar cases via SDK: