3/24/2024 0 Comments Refit0.14 & tuxera ntfs 2015initial_configurations_via_metalearning int, optional (default=25) That typical machine learning algorithms can be fit on the Model fitting will be terminated if the machine learningĪlgorithm runs over the time limit. Time limit for a single call to the machine learning model. ![]() per_run_time_limit int, optional (default=1/10 of time_left_for_this_task) ![]() By increasing this value, auto-sklearn has a higherĬhance of finding better models. Time limit in seconds for the search of appropriate Parameters time_left_for_this_task int, optional (default=3600) This class implements the classification task. ![]() AutoSklearnClassifier ( time_left_for_this_task = 3600, per_run_time_limit = None, initial_configurations_via_metalearning = 25, ensemble_size : int = 50, ensemble_nbest = 50, max_models_on_disc = 50, seed = 1, memory_limit = 3072, include : Optional ] ] = None, exclude : Optional ] ] = None, resampling_strategy = 'holdout', resampling_strategy_arguments = None, tmp_folder = None, delete_tmp_folder_after_terminate = True, n_jobs : Optional = None, dask_client : Optional = None, disable_evaluator_output = False, get_smac_object_callback = None, smac_scenario_args = None, logging_config = None, metadata_directory = None, metric = None, scoring_functions : Optional ] = None, load_models : bool = True, get_trials_callback = None ) ¶ Classification ¶ class autosklearn.classification.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |