edaflow.ml.random_search_models

edaflow.ml.random_search_models(models: Dict[str, BaseEstimator], param_distributions: Dict[str, Dict[str, Any]], X_train: DataFrame, y_train: Series, n_iter: int = 50, cv: int = 5, scoring: str = 'auto', verbose: bool = True, random_state: int = 42) → Dict[str, Dict[str, Any]]

Perform random search optimization for multiple models.

Parameters:

modelsDict[str, BaseEstimator]

Dictionary of model name -> model pairs

param_distributionsDict[str, Dict[str, Any]]

Dictionary of model name -> parameter distributions pairs

X_trainpd.DataFrame

Training features

y_trainpd.Series

Training target

n_iterint, default=50

Number of random search iterations

cvint, default=5

Number of cross-validation folds

scoringstr, default=’auto’

Scoring metric

verbosebool, default=True

Whether to print progress

random_stateint, default=42

Random seed for reproducibility

Returns:

Dict[str, Dict[str, Any]]

Dictionary of model name -> optimization results pairs