streamline.runners.report_runner module

class streamline.runners.report_runner.ReportRunner(output_path=None, experiment_name=None, experiment_path=None, algorithms=None, exclude=('XCS', 'eLCS'), training=True, rep_data_path=None, dataset_for_rep=None, run_cluster=False, queue='defq', reserved_memory=4)

Bases: object

Runner Class for collating dataset compare job

Parameters:

• output_path – path to output directory

• experiment_name – name of experiment (no spaces)

• algorithms – list of str of ML models to run

• training – Indicate True or False for whether to generate pdf summary for pipeline training or followup application analysis to new dataset,default=True

• rep_data_path – path to directory containing replication or hold-out testing datasets (must have at least all features with same labels as in original training dataset),default=None

• dataset_for_rep – path to target original training dataset

get_cluster_params()

run(run_parallel=False)

submit_lsf_cluster_job()

submit_slurm_cluster_job()