Explainable Stock Forecasting Engine
Interpretable ML for stock price prediction with feature importance and model explanation techniques
Stock price forecasting system focused on explainability and transparency — not just predicting prices, but understanding why the model made each prediction.
What I built:
- Feature importance analysis using SHAP values to interpret model decisions
- Ensemble of ML models benchmarked on historical financial data
- Visualization of feature impact across different market conditions
Tech stack: Python · Pandas · NumPy · Scikit-learn · SHAP · Matplotlib