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25 lines
1010 B
Python
25 lines
1010 B
Python
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import pandas as pd
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from utils.evaluate import evaluate_predictions
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def average_and_evaluate_predictions(predictions: pd.DataFrame, y: pd.Series, target_returns: pd.Series, data_config: dict) -> tuple[pd.Series, pd.DataFrame]:
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averaged_predictions = predictions.mean(axis = 1)
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non_discretized_result = evaluate_predictions(
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model_name = 'Averaged - Non-discrete',
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target_returns = target_returns,
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y_pred = averaged_predictions,
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y_true = y,
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method = 'classification',
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no_of_classes = data_config['no_of_classes'],
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discretize=False
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)
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discretized_result = evaluate_predictions(
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model_name = 'Averaged - Discrete',
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target_returns = target_returns,
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y_pred = averaged_predictions,
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y_true = y,
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method = 'classification',
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no_of_classes = data_config['no_of_classes'],
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discretize=True
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)
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return averaged_predictions, pd.concat([non_discretized_result, discretized_result], axis = 1)
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