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feat: enhance training workflow with model metadata loading and refactor data handling

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- Introduced a new activity to load model metadata from the model store.
- Refactored training logic to utilize new model metadata and improved parameter handling.
- Updated the `TrainModelParams` class to include additional fields for model configuration.
- Replaced deprecated utility functions with a custom train-test split implementation.
- Removed unused utility functions and cleaned up the data manager repository.
- Adjusted experiment tracking to include model-specific metadata in notifications.
This commit is contained in:
vitor-aignosi
2026-03-24 14:39:28 -03:00
parent cf5111e520
commit 342a02d6f7
13 changed files with 242 additions and 465 deletions
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10
model_manager/utils/models/train_model_result.py
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@@ -34,12 +34,10 @@ class TrainModelResult:
"""
params: TrainModelParams
x_train: pd.DataFrame
x_test: pd.DataFrame
y_train: pd.Series
y_test: pd.Series
y_pred: pd.Series | None = None
y_train_pred: pd.Series | None = None
train_data: pd.DataFrame
val_data: pd.DataFrame
y_pred: pd.DataFrame | None = None
y_train_pred: pd.DataFrame | None = None
mse_val: float | None = None
mae_val: float | None = None
r2_val: float | None = None