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44 lines
1.3 KiB
44 lines
1.3 KiB
3 weeks ago
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"""
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Stock 15-minute return prediction experiments.
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This module provides dataset loading and experiment utilities for
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stock 15-minute (intraday) return prediction.
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Example:
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>>> from alpha_lab.stock_15m import Stock15mLoader
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>>>
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>>> loader = Stock15mLoader(
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... normalization_mode='dual',
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... positive_factor=1.0,
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... negative_factor=2.0
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... )
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>>> dataset = loader.load(
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... dt_range=['2020-01-01', '2023-12-31'],
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... feature_path='/data/parquet/stock_1min_alpha158',
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... kline_path='/data/parquet/stock_1min_kline'
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... )
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>>>
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>>> # Extract training data
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>>> X_train, y_train, w_train = dataset.to_numpy()
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Training:
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>>> from alpha_lab.stock_15m import train_model, TrainConfig
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>>>
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>>> config = TrainConfig(
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... dt_range=['2020-01-01', '2023-12-31'],
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... feature_path='/data/parquet/stock_1min_alpha158',
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... kline_path='/data/parquet/stock_1min_kline'
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... )
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>>> model, metrics = train_model(config, output_dir='results/exp01')
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"""
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# Re-export all public APIs from src submodules
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from .src import Stock15mLoader
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try:
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from .src import train_model, TrainConfig
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__all__ = ['Stock15mLoader', 'train_model', 'TrainConfig']
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except ImportError:
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# xgboost or sklearn not installed
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__all__ = ['Stock15mLoader']
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