55 lines
2.6 KiB
Python
55 lines
2.6 KiB
Python
from dataclasses import dataclass
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import pandas as pd
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from model_manager.sientia.models import DataPreprocessor, LinearRegressionModel
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from model_manager.utils.models.train_model_params import TrainModelParams
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@dataclass
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class TrainModelResult:
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"""
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A data container for storing the results of a machine learning training process.
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This dataclass encapsulates all outputs from the training pipeline, including
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the trained model, datasets, evaluation metrics, and paths to generated artifacts.
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It is used to pass results between activities in the training workflow.
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Attributes:
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params (TrainModelParams): The parameters used to train the model.
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process_data (DataPreprocessor): The data preprocessor object used to process the input data.
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x_train (pd.DataFrame): The training dataset features.
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x_test (pd.DataFrame): The testing dataset features.
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y_train (pd.DataFrame): The training dataset target values.
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y_test (pd.DataFrame): The testing dataset target values.
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regr (LinearRegressionModel): The trained linear regression model.
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scaler_dict (dict): A dictionary containing the scalers used to scale the features and target values.
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y_pred (pd.Series | None): The predicted target values for the testing dataset. Default is None.
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mse_val (float | None): The Mean Squared Error (MSE) of the predictions. Default is None.
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mae_val (float | None): The Mean Absolute Error (MAE) of the predictions. Default is None.
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r2_val (float | None): The R-squared (R²) value of the predictions. Default is None.
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run_name (str | None): The name of the MLFlow run. Default is None.
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report_path (str | None): The path to the generated HTML report file. Default is None.
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train_data_path (str | None): The path to the training dataset CSV file. Default is None.
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test_data_path (str | None): The path to the testing dataset CSV file. Default is None.
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run_dir (str | None): The path to the run directory containing all artifacts. Default is None.
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"""
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params: TrainModelParams
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process_data: DataPreprocessor
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x_train: pd.DataFrame
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x_test: pd.DataFrame
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y_train: pd.Series
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y_test: pd.Series
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regr: LinearRegressionModel
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scaler_dict: dict
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y_pred: pd.Series | None = None
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mse_val: float | None = None
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mae_val: float | None = None
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r2_val: float | None = None
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run_name: str | None = None
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report_path: str | None = None
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train_data_path: str | None = None
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test_data_path: str | None = None
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run_dir: str | None = None
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