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expose nu in the SVM outlier detection via svm_nu in config

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robcaulk
2022-06-28 15:12:25 +02:00
parent 7dfbd432d1
commit 6c7d02cb18
2 changed files with 4 additions and 3 deletions
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5
freqtrade/freqai/data_kitchen.py
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@@ -572,7 +572,8 @@ class FreqaiDataKitchen:
else:
# use SGDOneClassSVM to increase speed?
self.svm_model = linear_model.SGDOneClassSVM(nu=0.1).fit(
nu = self.freqai_config.get('feature_parameters', {}).get('svm_nu', 0.2)
self.svm_model = linear_model.SGDOneClassSVM(nu=nu).fit(
self.data_dictionary["train_features"]
)
y_pred = self.svm_model.predict(self.data_dictionary["train_features"])
@@ -742,7 +743,7 @@ class FreqaiDataKitchen:
max_time = self.freqai_config.get('expiration_hours', 0)
if max_time > 0:
return elapsed_time > max_time
else:
else:
return False
def check_if_new_training_required(self, trained_timestamp: int) -> Tuple[bool,