To end the reign of terror of ants and bees within the universum of heuristics, we introduce BumbleBO.
BumbleBO is a framework for Bayesian Optimization that supports almost all regressor models from sklearn, i.e. about 50 different models, as surrogate models. The acquisiton function is optimized using multi-objective heuristics from pymoo and resampling-based uncertainty measures (todo!).