load_and_run_forecasting_experiment

tsml_eval.experiments.load_and_run_forecasting_experiment(problem_path, results_path, dataset, forecaster, forecaster_name=None, random_seed=None, write_attributes=False, att_max_shape=0, benchmark_time=True, overwrite=False)

Load a dataset and run a regression experiment.

Function to load a dataset, run a basic regression experiment for a <dataset>/<regressor/<resample> combination, and write the results to csv file(s) at a given location.

Parameters:

problem_pathstr

Location of problem files, full path.

results_pathstr

Location of where to write results. Any required directories will be created.

datasetstr

Name of problem. Files must be <problem_path>/<dataset>/<dataset>+”_TRAIN.csv”, same for “_TEST.csv”.

forecasterBaseForecaster

Regressor to be used in the experiment.

forecaster_namestr or None, default=None

Name of forecaster used in writing results. If None, the name is taken from the forecaster.

random_seedint or None, default=None

Indicates what random seed was used as a random_state for the forecaster. Only used for the results file name.

benchmark_timebool, default=True

Whether to benchmark the hardware used with a simple function and write the results. This will typically take ~2 seconds, but is hardware dependent.

overwritebool, default=False

If set to False, this will only build results if there is not a result file already present. If True, it will overwrite anything already there.