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auto populate features based on a prepended % in the strategy (remove feature assignment from config). Update doc/constants/example strategy to reflect change

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This commit is contained in:
robcaulk
2022-05-17 18:15:03 +02:00
parent 8664e8f9a3
commit d1d451c27e
6 changed files with 80 additions and 69 deletions
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5
freqtrade/freqai/prediction_models/CatboostPredictionModel.py
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@@ -53,9 +53,8 @@ class CatboostPredictionModel(IFreqaiModel):
logger.info("--------------------Starting training--------------------")
# create the full feature list based on user config info
self.dh.training_features_list = self.dh.build_feature_list(self.config, metadata)
self.dh.training_features_list = self.dh.find_features(unfiltered_dataframe)
unfiltered_labels = self.make_labels(unfiltered_dataframe)
# filter the features requested by user in the configuration file and elegantly handle NaNs
features_filtered, labels_filtered = self.dh.filter_features(
unfiltered_dataframe,
@@ -127,7 +126,7 @@ class CatboostPredictionModel(IFreqaiModel):
# logger.info("--------------------Starting prediction--------------------")
original_feature_list = self.dh.build_feature_list(self.config, metadata)
original_feature_list = self.dh.find_features(unfiltered_dataframe)
filtered_dataframe, _ = self.dh.filter_features(
unfiltered_dataframe, original_feature_list, training_filter=False
)