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View sklearn_pipe.py
# train_dataset: pd.DataFrame
# Columns
# numerical_features = ["close_percent_bb", "macd_diff", "force_index"] ,
# type: float
# categorical_features = ["previous_day_flag"]
# type: str
# value from set {"up", "down", "flat"}
# Example:
# >>train_dataset.loc[:, numerical_features + categorical_features + ["label"]].head(5)
# percent_bb macd_diff force_index previous_day_flag label
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adamnovotnycom / berkeley_earth_temp_data.ipynb
Last active Apr 18, 2021
berkeley_earth_temp_data.ipynb
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adamnovotnycom / lstm_synthetic_data.ipynb
Last active Nov 14, 2021
lstm_synthetic_data.ipynb
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