OHLCVPredictor/INFERENCE_README.md

# OHLCV Predictor - Inference (Quick Reference)

For full instructions, see the main README.

## Minimal usage

```python
from predictor import OHLCVPredictor

predictor = OHLCVPredictor('../data/xgboost_model_all_features.json')
predictions = predictor.predict(your_ohlcv_dataframe)
```

Your DataFrame needs these columns:
- `Timestamp`, `Open`, `High`, `Low`, `Close`, `Volume`, `log_return`

Note: If you are only running inference (not training with `main.py`), compute `log_return` first:

```python
import numpy as np
df['log_return'] = np.log(df['Close'] / df['Close'].shift(1))
```

## Files to reuse in other projects

- `predictor.py`
- `custom_xgboost.py`
- `feature_engineering.py`
- `technical_indicator_functions.py`
- your trained model file (e.g., `xgboost_model_all_features.json`)
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00			`# OHLCV Predictor - Inference (Quick Reference)`
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects. 2025-08-08 09:38:18 +08:00
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00			`For full instructions, see the main README.`
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects. 2025-08-08 09:38:18 +08:00
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00			`## Minimal usage`
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects. 2025-08-08 09:38:18 +08:00
			```python
			`from predictor import OHLCVPredictor`

Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00			`predictor = OHLCVPredictor('../data/xgboost_model_all_features.json')`
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects. 2025-08-08 09:38:18 +08:00			`predictions = predictor.predict(your_ohlcv_dataframe)`
			```

			`Your DataFrame needs these columns:`
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00			- `Timestamp`, `Open`, `High`, `Low`, `Close`, `Volume`, `log_return`
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects. 2025-08-08 09:38:18 +08:00
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00			Note: If you are only running inference (not training with `main.py`), compute `log_return` first:
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects. 2025-08-08 09:38:18 +08:00
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00			```python
			`import numpy as np`
			`df['log_return'] = np.log(df['Close'] / df['Close'].shift(1))`
Enhance CustomXGBoostGPU for inference by making training data optional and adding model loading functionality. Update feature engineering to support caching and improve data handling. Introduce a new inference example and README for better usability in other projects. 2025-08-08 09:38:18 +08:00			```
Update inference documentation and main script for improved usability. Revise README for clarity on data requirements and minimal usage. Adjust main.py to ensure proper handling of test predictions and add checks for local variables before plotting. 2025-08-12 15:12:07 +08:00
			`## Files to reuse in other projects`

			- `predictor.py`
			- `custom_xgboost.py`
			- `feature_engineering.py`
			- `technical_indicator_functions.py`
			- your trained model file (e.g., `xgboost_model_all_features.json`)