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freqai_info -> ft_params
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@ -141,7 +141,7 @@ class PyTorchTransformerRegressor(BasePyTorchRegressor):
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pred_df = pd.DataFrame(yb.detach().numpy(), columns=dk.label_list)
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pred_df = pd.DataFrame(yb.detach().numpy(), columns=dk.label_list)
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pred_df, _, _ = dk.label_pipeline.inverse_transform(pred_df)
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pred_df, _, _ = dk.label_pipeline.inverse_transform(pred_df)
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if self.freqai_info.get("DI_threshold", 0) > 0:
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if self.ft_params.get("DI_threshold", 0) > 0:
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dk.DI_values = dk.feature_pipeline["di"].di_values
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dk.DI_values = dk.feature_pipeline["di"].di_values
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else:
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else:
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dk.DI_values = np.zeros(outliers.shape[0])
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dk.DI_values = np.zeros(outliers.shape[0])
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