Bruno Domingues 06fd08dc70 SIENTIAPDE-1430: Introduce comprehensive integration testing with JSON-based scenarios and detailed README documentation. Enhance training workflow to support advanced model configurations, including polynomial regression with mandatory scaler validation. Ensure robust prediction handling by calculating training predictions (y_train_pred) before denormalization and automatically configuring datetime indices for time-series operations.

2025-12-18 17:05:10 -03:00

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__init__.py

SIENTIAPDE-1250: Refactor: Remove 'laborious' directory from test structure and update README.md accordingly.

2025-10-07 10:02:38 -03:00

test_experiment_status.py

SIENTIAPDE-1309: Update README with Helm instructions and refactor experiment status messages. Also, update values.yaml with new image and configurations.

2025-11-06 15:34:03 -03:00

test_init.py

SIENTIAPDE-1309: Update README with Helm instructions and refactor experiment status messages. Also, update values.yaml with new image and configurations.

2025-11-06 15:34:03 -03:00

test_train_model_params.py

SIENTIAPDE-1430: Implement advanced model training capabilities and enhanced data preprocessing. This includes support for Polynomial Regression with configurable degree and interaction terms, flexible per-variable lag configurations, and new data filtering options by date range and removed intervals. Comprehensive business validations are now enforced for all parameters, and MLflow logging has been extended to capture these detailed configurations. Additionally, Reduced Coulomb Energy (RCE) metrics are added for drift detection, with a new changelog documenting all pipeline parameter updates.

2025-12-17 21:39:43 -03:00

test_train_model_result.py

SIENTIAPDE-1430: Introduce comprehensive integration testing with JSON-based scenarios and detailed README documentation. Enhance training workflow to support advanced model configurations, including polynomial regression with mandatory scaler validation. Ensure robust prediction handling by calculating training predictions (y_train_pred) before denormalization and automatically configuring datetime indices for time-series operations.

2025-12-18 17:05:10 -03:00