11 Commits

Author	SHA1	Message	Date
Kou Kinoshita	a4d94dd2ff	SIENTIAPDE-1579: Added date format and convert methods	2026-02-13 18:41:46 -03:00
Bruno Domingues	06571011f2	SIENTIAPDE-1430: Introduce static_threshold parameter for static window removal. ... This parameter allows customizing the threshold (1-1000) used when rem_static_win is enabled, defaulting to 1 if null. Updates include parameter definition, business rule validation, repository logic for passing the threshold, documentation in README.md and PIPELINE_PARAMS_CHANGELOG.md, and new unit and integration tests.	2025-12-19 15:44:18 -03:00
Bruno Domingues	7cbb7022e5	SIENTIAPDE-1430: Refactor DataPreprocessor date filtering, make rce_train radius optional, and introduce constants for model names.	2025-12-19 12:28:07 -03:00
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
Bruno Domingues	6e8f87b2a3	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
Bruno Domingues	94697215aa	SIENTIAPDE-1241: Refactor: Improve documentation, exception handling, and configuration in model manager. This commit enhances clarity and robustness by adding detailed docstrings to methods, standardizing exception handling with custom types, and simplifying MLflow configuration.	2025-10-22 21:48:12 -03:00
Bruno Domingues	5789a13023	SIENTIAPDE-1241: refactor train_model workflow due to I/O errors.	2025-10-22 15:37:56 -03:00
Bruno Domingues	305a39b44c	SIENTIAPDE-1253: Implement business rule validation for training parameters. Adds a validate_business_rules method to the TrainModelParams class to enforce constraints on training parameters, improving data integrity and preventing errors. Also updates tests to include target variable in variable columns and adds tests for business rule validations.	2025-10-15 16:16:09 -03:00
Bruno Domingues	94e11df803	SIENTIAPDE-1252: Remove experiment_description from TrainModelParams and related tests.	2025-10-09 17:48:43 -03:00
Bruno Domingues	04c94efd98	SIENTIAPDE-1249: Refactor TrainModelParams to use dataclass and add from_dict method for validation, remove no-cache-dir from pip install in quality gate workflow, and rename X_train/X_test to x_train/x_test in TrainModelResult.	2025-10-06 19:11:02 -03:00
Bruno Domingues	d8583cdae7	SIENTIAPDE-1249: Implement data models for Model Manager and add unit tests. This commit introduces data transfer objects (DTOs) and model classes for experiment status, training parameters, and training results, along with corresponding unit tests to ensure their correct behavior.	2025-10-06 16:49:18 -03:00