Update mal-formatted docstrings
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@@ -26,9 +26,8 @@ class XGBoostRFClassifier(BaseClassifierModel):
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def fit(self, data_dictionary: Dict, dk: FreqaiDataKitchen, **kwargs) -> Any:
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"""
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User sets up the training and test data to fit their desired model here
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:params:
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:data_dictionary: the dictionary constructed by DataHandler to hold
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all the training and test data/labels.
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:param data_dictionary: the dictionary constructed by DataHandler to hold
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all the training and test data/labels.
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"""
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X = data_dictionary["train_features"].to_numpy()
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@@ -65,7 +64,7 @@ class XGBoostRFClassifier(BaseClassifierModel):
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) -> Tuple[DataFrame, npt.NDArray[np.int_]]:
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"""
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Filter the prediction features data and predict with it.
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:param: unfiltered_df: Full dataframe for the current backtest period.
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:param unfiltered_df: Full dataframe for the current backtest period.
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:return:
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:pred_df: dataframe containing the predictions
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:do_predict: np.array of 1s and 0s to indicate places where freqai needed to remove
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