get_classifier_by_name

tsml_eval.experiments.get_classifier_by_name(classifier_name, random_state=None, n_jobs=1, fit_contract=0, checkpoint=None, **kwargs)

Return a classifier matching a given input name.

Basic way of creating a classifier to build using the default or alternative settings. This set up is to help with batch jobs for multiple problems and to facilitate easy reproducibility for use with run_classification_experiment.

Generally, inputting a classifier class name will return said classifier with default settings.

Parameters:

classifier_namestr

String indicating which classifier to be returned.

random_stateint, RandomState instance or None, default=None

Random seed or RandomState object to be used in the classifier if available.

n_jobs: int, default=1

The number of jobs to run in parallel for both classifier fit and predict if available. -1 means using all processors.

fit_contract: int, default=0

Contract time in minutes for classifier fit if available.

checkpoint: str or None, default=None

Path to a checkpoint file to save the classifier if available. No checkpointing if None.

**kwargs

Additional keyword arguments to be passed to the classifier.