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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.

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Bruno Domingues
2025-12-18 17:05:10 -03:00
parent 6e8f87b2a3
commit 06fd08dc70
18 changed files with 631 additions and 37 deletions
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6
model_manager/utils/models/train_model_params.py
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@@ -248,6 +248,12 @@ class TrainModelParams:
f'degree must be at least 2 for Polynomial Regression, got {self.degree}'
)
if self.model_name == 'Polynomial Regression' and self.scaler_name == 'None':
raise ValueError(
'scaler_name must be set (e.g., "Standard Scaler") for Polynomial Regression '
'to avoid numerical overflow with large feature values'
)
if self.model_name == 'Linear Regression' and self.degree != 1:
raise ValueError(f'degree must be 1 for Linear Regression, got {self.degree}')

2
model_manager/utils/models/train_model_result.py
View File

@@ -25,6 +25,7 @@ class TrainModelResult:
regr (LinearRegressionModel): The trained linear regression model.
scaler_dict (dict): A dictionary containing the scalers used to scale the features and target values.
y_pred (pd.Series | None): The predicted target values for the testing dataset. Default is None.
y_train_pred (pd.Series | None): The predicted target values for the training dataset. Default is None.
mse_val (float | None): The Mean Squared Error (MSE) of the predictions. Default is None.
mae_val (float | None): The Mean Absolute Error (MAE) of the predictions. Default is None.
r2_val (float | None): The R-squared (R²) value of the predictions. Default is None.
@@ -46,6 +47,7 @@ class TrainModelResult:
regr: LinearRegressionModel
scaler_dict: dict
y_pred: pd.Series | None = None
y_train_pred: pd.Series | None = None
mse_val: float | None = None
mae_val: float | None = None
r2_val: float | None = None