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Merge pull request #1 from lolongcovas/refactor_set_weights_higher_recent

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Refactor set weights higher recent
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lolong 2022-07-19 00:16:23 +02:00 committed by GitHub
commit c10c962f1b
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2 changed files with 7 additions and 6 deletions
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8
freqtrade/freqai/data_kitchen.py
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@ -675,12 +675,10 @@ class FreqaiDataKitchen:
Set weights so that recent data is more heavily weighted during Set weights so that recent data is more heavily weighted during
training than older data. training than older data.
""" """
wfactor = self.config["freqai"]["feature_parameters"]["weight_factor"]
weights = np.zeros(num_weights) weights = np.zeros(num_weights)
for i in range(1, len(weights)): weights[1:] = np.exp(
weights[len(weights) - i] = np.exp( - np.arange(1, len(weights)) / (wfactor * num_weights))[::-1]
-i / (self.config["freqai"]["feature_parameters"]["weight_factor"] * num_weights)
)
return weights return weights
def append_predictions(self, predictions, do_predict, len_dataframe): def append_predictions(self, predictions, do_predict, len_dataframe):

5
freqtrade/freqai/prediction_models/BaseRegressionModel.py
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@ -39,7 +39,10 @@ class BaseRegressionModel(IFreqaiModel):
:model: Trained model which can be used to inference (self.predict) :model: Trained model which can be used to inference (self.predict)
""" """
logger.info("--------------------Starting training " f"{pair} --------------------") start_date = unfiltered_dataframe["date"].iloc[0]
end_date = unfiltered_dataframe["date"].iloc[-1]
logger.info("-------------------- Starting training " f"{pair} --------------------")
logger.info("-------------------- Using data " f"from {start_date} to {end_date}--------------------")
# filter the features requested by user in the configuration file and elegantly handle NaNs # filter the features requested by user in the configuration file and elegantly handle NaNs
features_filtered, labels_filtered = dk.filter_features( features_filtered, labels_filtered = dk.filter_features(