adaptive.run_adaptive_search

run_adaptive_search(
    executor,
    input_cols,
    outcome_col,
    ranges,
    existing_data=None,
    n_start=20,
    n_step=10,
    max_iter=5,
    max_hours=None,
)

Orchestrates the Active Learning loop on raw DataFrames using the Executor architecture.

Parameters

Name	Type	Description	Default
executor	Executor \| str	An instance of an Executor (Python, CLI, Matlab). Accepts a legacy command string for backward compatibility.	required
input_cols	List[str]	Input names.	required
outcome_col	str	Outcome name.	required
ranges	Dict	Input bounds.	required
existing_data	pd.DataFrame	Start data.	`None`
n_start	int	Init batch size.	`20`
n_step	int	Points added per refinement step.	`10`
max_iter	int	Max loops.	`5`
max_hours	float	Physical time limit in hours.	`None`

Returns

Name	Type	Description
	pd.DataFrame	pd.DataFrame: Final dataset containing all successful runs.