feat: enhance data fetching and model training with OI and funding rate integration
- Updated `fetch_history.py` to collect open interest (OI) and funding rate data from Binance, improving the dataset for model training. - Modified `train_and_deploy.sh` to include options for OI and funding rate collection during data fetching. - Enhanced `dataset_builder.py` to incorporate OI change and funding rate features with rolling z-score normalization. - Updated training logs to reflect new metrics and features, ensuring comprehensive tracking of model performance. - Adjusted feature columns in `ml_features.py` to include OI and funding rate for improved model robustness.
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@@ -8,6 +8,9 @@ FEATURE_COLS = [
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"btc_ret_1", "btc_ret_3", "btc_ret_5",
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"eth_ret_1", "eth_ret_3", "eth_ret_5",
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"xrp_btc_rs", "xrp_eth_rs",
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# 시장 미시구조: OI 변화율(z-score), 펀딩비(z-score)
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# parquet에 oi_change/funding_rate 컬럼이 없으면 dataset_builder에서 0으로 채움
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"oi_change", "funding_rate",
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]
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