def start_b(data_set_name, file_name=None, models_to_run=None, models_to_run_2=MLP_MODELS, ensembles=ENSEMBLES): # change to None to choose from console """ starts benchmark """ if models_to_run == 'SLM_MODELS': models_to_run = SLM_MODELS if models_to_run == 'MLP_MODELS': models_to_run = MLP_MODELS if models_to_run_2 == 'SLM_MODELS': models_to_run_2 = SLM_MODELS if models_to_run_2 == 'MLP_MODELS': models_to_run_2 = MLP_MODELS # SLM MODELS if models_to_run is not None: benchmarker = Benchmarker(data_set_name, models=models_to_run, ensembles=ensembles, benchmark_id='slm') # benchmarker.run() benchmarker.run_nested_cv() # MLP MODELS if models_to_run_2 is not None: benchmarker = Benchmarker(data_set_name, models=models_to_run_2, ensembles=ensembles, benchmark_id='mlp') benchmarker.run_nested_cv()
def start_slm(data_set_name, ensembles=ENSEMBLES, benchmark_id='slm'): benchmarker = Benchmarker(data_set_name, models=SLM_MODELS, ensembles=ensembles, benchmark_id=benchmark_id) benchmarker.run_nested_cv()