Probabilistic Modelling & Simulation
Enable reinforcement learning, probabilistic modelling, and optimisation techniques to explore complex operational dynamics and improve decision support through repeated simulation and analysis.
Ensemble ML pipeline (60% logistic regression + 40% decision stump forest) with isotonic calibration produces calibrated probability estimates. Monte Carlo simulation (10,000 iterations) tests model fitness. Walk-forward temporal validation ensures out-of-sample reliability. Confidence intervals via bootstrap resampling.