Random Forest Calibrated Pipeline

From BallesJr/polymarket-edge-model, this is a systematic trading pipeline built around Random Forest machine learning models calibrated for probability estimation on Polymarket. The repo includes full backtesting infrastructure, feature engineering for prediction market data, and calibrated probability outputs to identify mispriced markets. The approach likely focuses on identifying markets where Polymarket implied probabilities deviate from model-estimated probabilities. The pipeline outputs trade signals with confidence levels. Requires Python environment with ML dependencies. Risk is moderate; model overfitting is a primary concern given prediction market dynamics.