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ensure outlier-check is returning as a numpy array from datasieve

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robcaulk
2023-06-25 15:43:02 +02:00
parent 5f98530ef9
commit fd420738cd
8 changed files with 8 additions and 8 deletions
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2
freqtrade/freqai/base_models/BaseClassifierModel.py
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@@ -121,6 +121,6 @@ class BaseClassifierModel(IFreqaiModel):
dk.DI_values = dk.feature_pipeline["di"].di_values
else:
dk.DI_values = np.zeros(len(outliers.index))
dk.do_predict = outliers.to_numpy()
dk.do_predict = outliers
return (pred_df, dk.do_predict)

2
freqtrade/freqai/base_models/BasePyTorchClassifier.py
View File

@@ -95,7 +95,7 @@ class BasePyTorchClassifier(BasePyTorchModel):
dk.DI_values = dk.feature_pipeline["di"].di_values
else:
dk.DI_values = np.zeros(len(outliers.index))
dk.do_predict = outliers.to_numpy()
dk.do_predict = outliers
return (pred_df, dk.do_predict)

2
freqtrade/freqai/base_models/BasePyTorchRegressor.py
View File

@@ -56,7 +56,7 @@ class BasePyTorchRegressor(BasePyTorchModel):
dk.DI_values = dk.feature_pipeline["di"].di_values
else:
dk.DI_values = np.zeros(len(outliers.index))
dk.do_predict = outliers.to_numpy()
dk.do_predict = outliers
return (pred_df, dk.do_predict)
def train(

2
freqtrade/freqai/base_models/BaseRegressionModel.py
View File

@@ -115,6 +115,6 @@ class BaseRegressionModel(IFreqaiModel):
dk.DI_values = dk.feature_pipeline["di"].di_values
else:
dk.DI_values = np.zeros(len(outliers.index))
dk.do_predict = outliers.to_numpy()
dk.do_predict = outliers
return (pred_df, dk.do_predict)