mirror of
https://github.com/webclinic017/drift.git
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Mark Aron Szulyovszky
2606639cc2
* fix(Labelling): didn't forward shift forward returns previously, introduced major lookahead bias * fix(Baseline): use the same config
67 lines
2.0 KiB
Python
67 lines
2.0 KiB
Python
from sklearn.model_selection import train_test_split
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from config.types import Config, RawConfig
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from config.preprocess import preprocess_config
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from config.presets import get_default_config, get_minimal_config
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from data_loader.load import load_data
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from data_loader.process import check_data
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from labeling.process import label_data
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from sklearn.metrics import accuracy_score
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def run_sklearn_pipeline(raw_config: RawConfig):
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config = preprocess_config(raw_config)
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run_sklearn_training(config)
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def run_sklearn_training(config: Config):
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print("---> Load data, check for validity")
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X, returns = load_data(
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assets=config.assets,
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other_assets=config.other_assets,
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exogenous_data=config.exogenous_data,
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target_asset=config.target_asset,
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load_non_target_asset=config.load_non_target_asset,
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own_features=config.own_features,
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other_features=config.other_features,
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exogenous_features=config.exogenous_features,
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start_date=config.start_date,
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)
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assert check_data(X, config) == True, "Data is not valid."
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print("---> Filter for significant events when we want to trade, and label data")
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events, X, y, forward_returns = label_data(
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event_filter=config.event_filter,
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event_labeller=config.labeling,
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X=X,
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returns=returns,
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remove_overlapping_events=config.remove_overlapping_events,
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)
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X_train, X_test, y_train, y_test = train_test_split(
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X, y, test_size=0.2, random_state=42, shuffle=False
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)
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print("---> Train directional models")
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for transformation in config.transformations:
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X_train = transformation.fit_transform(X_train, y_train)
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for transformation in config.transformations:
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X_test = transformation.transform(X_test)
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config.directional_model.fit(X_train, y_train)
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preds = config.directional_model.predict(X_test)
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print(accuracy_score(y_test, preds))
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if __name__ == "__main__":
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run_sklearn_pipeline(
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raw_config=get_default_config(),
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)
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