autoprognosis.explorers.core.optimizer module

class EnsembleOptimizer(study_name: str, ensemble_len: int, evaluation_cbk: Callable, optimizer_type: str = 'bayesian', n_trials: int = 50, timeout: int = 60, max_iter: int = 27, eta: int = 3, skip_recap: bool = False, random_state: int = 0)

Bases: object

evaluate() → Tuple[float, dict]

class Optimizer(study_name: str, estimator: Any, evaluation_cbk: Callable, optimizer_type: str = 'bayesian', n_trials: int = 50, timeout: int = 60, eta: int = 3, random_state: int = 0)

Bases: object

evaluate() → Tuple[List[float], List[dict]]