edaflow.ml.random_search_modelsο
- 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]][source]ο
Perform random search optimization for multiple models.
Parameters:ο
- 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=βautoβ
Scoring metric
- verbosebool, default=True
Whether to print progress
- random_stateint, default=42
Random seed for reproducibility
Returns:ο
- Dict[str, Dict[str, Any]]
Dictionary of model name -> optimization results pairs