Bruno Domingues
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6e8f87b2a3
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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.
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2025-12-17 21:39:43 -03:00 |
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Bruno Domingues
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94697215aa
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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.
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2025-10-22 21:48:12 -03:00 |
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Bruno Domingues
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5789a13023
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SIENTIAPDE-1241: refactor train_model workflow due to I/O errors.
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2025-10-22 15:37:56 -03:00 |
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Bruno Domingues
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305a39b44c
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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.
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2025-10-15 16:16:09 -03:00 |
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Bruno Domingues
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94e11df803
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SIENTIAPDE-1252: Remove experiment_description from TrainModelParams and related tests.
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2025-10-09 17:48:43 -03:00 |
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Bruno Domingues
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04c94efd98
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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.
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2025-10-06 19:11:02 -03:00 |
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Bruno Domingues
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d8583cdae7
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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.
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2025-10-06 16:49:18 -03:00 |
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