def main(basename, input_dir, params):
output_dir = os.getcwd()
D = store_and_or_load_data(data_dir=input_dir,
dataset=basename,
outputdir=output_dir)
cs = get_class(D.info).get_hyperparameter_search_space()
configuration = configuration_space.Configuration(cs, **params)
global evaluator
evaluator = HoldoutEvaluator(
datamanager=D,
configuration=configuration,
with_predictions=True,
all_scoring_functions=True,
output_dir=output_dir)
evaluator.fit()
evaluator.finish_up()
def make_mode_holdout(data, seed, configuration, num_run):
try:
debug_log("Run: %s" % make_mode_holdout.__name__)
evaluator = HoldoutEvaluator(data, configuration,
seed=seed,
num_run=num_run,
**_get_base_dict())
debug_log("Fit evaluator")
evaluator.fit()
signal.signal(15, empty_signal_handler)
debug_log("Fit finish up")
evaluator.finish_up()
model_directory = os.path.join(os.getcwd(), 'models_%d' % seed)
debug_log("Check model directory: %s" % model_directory)
assert os.path.exists(
model_directory), "Not found model directory: %s" % model_directory
debug_log("Save models in files")
model_filename = os.path.join(model_directory,
'%s.model' % num_run)
with open(model_filename, 'w') as fh:
pickle.dump(evaluator.model, fh, -1)
except AssertionError as e:
debug_log(str(e))
