Refactor ModelMetrics to utilize DriftAnalysis for drift detection
- Replaced ModelAnalysis with DriftAnalysis in the ModelMetrics class to enhance drift detection capabilities.
- Updated method signatures and documentation to reflect the changes in target_name and return values.
- Adjusted data handling to ensure compatibility with the new analysis methods and improved clarity in the drift metrics dataframe preparation.
SIENTIAPDE-1646 Add new scheduling configurations and remove outdated documentation
- Introduced new scheduling configurations for minimal retrain, drift analysis, and simple metrics in `input_sample.json`.
- Removed obsolete documentation files related to drift analysis and E2E test reports to streamline project resources.
- Updated E2E tests for minimal retrain to enhance reporting and error handling during model retraining processes.
Update E2E test report and enhance drift analysis handling
- Updated the E2E test report metrics to reflect the latest test results, showing 47 collected tests with all passing.
- Removed outdated sections related to failed tests and their causes, streamlining the report.
- Implemented a regression fix in the drift analysis to handle empty merged frames, ensuring workflows skip export when no drift metrics are available.
- Enhanced the `insert_sample_data` and `insert_sample_prediction` functions to allow customizable timestamps for better test accuracy.
- Refactored E2E tests to improve clarity and maintainability, particularly in handling repeat scenarios with distinct timestamps.
Refactor ModelMetrics to utilize DriftAnalysis for drift detection
- Replaced ModelAnalysis with DriftAnalysis in the ModelMetrics class to enhance drift detection capabilities.
- Updated method signatures and documentation to reflect the changes in target_name and return values.
- Adjusted data handling to ensure compatibility with the new analysis methods and improved clarity in the drift metrics dataframe preparation.
