expose nu in the SVM outlier detection via svm_nu in config
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@@ -248,7 +248,7 @@ class IFreqaiModel(ABC):
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# append the historic data once per round
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if self.data_drawer.historic_data:
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dh.update_historic_data(strategy)
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logger.info(f'Updating historic data on pair {metadata["pair"]}')
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logger.debug(f'Updating historic data on pair {metadata["pair"]}')
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# if trainable, check if model needs training, if so compute new timerange,
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# then save model and metadata.
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