glassbox.orchestrator.randomized_search

RandomizedSearchCV for randomized search.

---

RandomizedSearchCV

RandomizedSearchCV(
    estimator,
    param_space,
    cv_engine,
    scoring_func,
    n_iter=10,
    time_budget=0.0,
)

Bases: BaseSearch

Randomized search over a parameter space.

Parameters:

Name	Type	Description	Default
estimator	BaseModel	The model to optimize.	required
param_space	Dict	Distribution for random search.	required
cv_engine	BaseSplitter	Cross-validation splitter.	required
scoring_func	Callable	Scoring function used to evaluate candidates.	required
n_iter	int	Number of random parameter candidates to evaluate.	10
time_budget	float	Maximum time budget for the search.	0.0

Source code in glassbox/orchestrator/randomized_search.py

def __init__(
    self,
    estimator: "BaseModel",
    param_space: Dict,
    cv_engine: "BaseSplitter",
    scoring_func: "Callable",
    n_iter: int = 10,
    time_budget: float = 0.0,
) -> None:
    super().__init__(estimator, param_space, cv_engine, scoring_func)
    self.n_iter: int = n_iter
    self.time_budget: float = time_budget