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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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Bruno Domingues
2025-10-06 19:11:02 -03:00
parent d8583cdae7
commit 04c94efd98
5 changed files with 153 additions and 136 deletions
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26
model_manager/utils/models/train_model_result.py
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@@ -19,27 +19,27 @@ class TrainModelResult:
Attributes:
params (TrainModelParams): The parameters used to train the model.
process_data (DataPreprocessor): The data preprocessor object used to process the input data.
X_train (pd.DataFrame): The training dataset features.
X_test (pd.DataFrame): The testing dataset features.
x_train (pd.DataFrame): The training dataset features.
x_test (pd.DataFrame): The testing dataset features.
y_train (pd.DataFrame): The training dataset target values.
y_test (pd.DataFrame): The testing dataset target values.
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 (Optional[pd.Series]): The predicted target values for the testing dataset. Default is None.
mse_val (Optional[float]): The Mean Squared Error (MSE) of the predictions. Default is None.
mae_val (Optional[float]): The Mean Absolute Error (MAE) of the predictions. Default is None.
r2_val (Optional[float]): The R-squared (R²) value of the predictions. Default is None.
run_name (Optional[str]): The name of the MLFlow run. Default is None.
report_path (Optional[str]): The path to the generated HTML report file. Default is None.
train_data_path (Optional[str]): The path to the training dataset CSV file. Default is None.
test_data_path (Optional[str]): The path to the testing dataset CSV file. Default is None.
run_dir (Optional[str]): The path to the run directory containing all artifacts. Default is None.
y_pred (pd.Series | None): The predicted target values for the testing 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.
run_name (str | None): The name of the MLFlow run. Default is None.
report_path (str | None): The path to the generated HTML report file. Default is None.
train_data_path (str | None): The path to the training dataset CSV file. Default is None.
test_data_path (str | None): The path to the testing dataset CSV file. Default is None.
run_dir (str | None): The path to the run directory containing all artifacts. Default is None.
"""
params: TrainModelParams
process_data: DataPreprocessor
X_train: pd.DataFrame
X_test: pd.DataFrame
x_train: pd.DataFrame
x_test: pd.DataFrame
y_train: pd.DataFrame
y_test: pd.DataFrame
regr: LinearRegressionModel