def main(job_id, params):
"""
Main hook for Spearmint.
:param job_id:
:param params:
:return:
"""
score = experiment(params=params, classifier_fn=linearSVM, n=default_n_trials, test=False, **dataset_args[default_dataset])
return score
def main(job_id, params):
"""
Main hook for Spearmint.
:param job_id:
:param params:
:return:
"""
score = experiment(job_id=job_id, params=params, classifier_fn=adaboost, n=default_n_trials, **dataset_args[default_dataset])
return score
def main(job_id, params):
"""
Main hook for Spearmint.
:param job_id:
:param params:
:return:
"""
score = experiment(job_id=job_id, params=params, classifier_fn=pca_lr, n=default_n_trials, test=False, **dataset_args[default_dataset])
return score
def main(job_id, params, side=default_side, dataset=default_dataset):
"""
Main hook for Spearmint.
:param job_id:
:param params:
:return:
"""
logging.basicConfig(level=logging.INFO)
score = experiment(params=params, classifier_fn=rbfSVM, structure=structure, side=side, dataset=dataset,
folds=folds, source_path=source_path, use_fused=use_fused, balance=balance, n=n_trials)
return score
def main(job_id, params, side=default_side, dataset=default_dataset):
"""
Main hook for Spearmint.
:param job_id:
:param params:
:return:
"""
logging.basicConfig(level=logging.INFO)
score = experiment(params=params,
classifier_fn=rbfSVM,
structure=structure,
side=side,
dataset=dataset,
folds=folds,
source_path=source_path,
use_fused=use_fused,
balance=balance,
n=n_trials)
return score
dataset=dataset,
folds=folds,
source_path=source_path,
use_fused=use_fused,
balance=balance,
n=n_trials)
return score
if __name__ == "__main__":
#arguments = docopt(__doc__)
held_out_test = True
job_id = 0
params = {'log_gamma': -1.69406367, 'log_C': -1.69406367}
if held_out_test:
experiment(params=params,
classifier_fn=rbfSVM,
structure=structure,
side=default_side,
dataset=default_dataset,
folds=folds,
source_path=source_path,
use_fused=use_fused,
balance=balance,
n=n_trials,
test=True)
else:
for side in sides:
for dataset in adni_datasets:
main(job_id, params, side, dataset)
Main hook for Spearmint.
:param job_id:
:param params:
:return:
"""
logging.basicConfig(level=logging.INFO)
score = experiment(params=params, classifier_fn=rbfSVM, structure=structure, side=side, dataset=dataset,
folds=folds, source_path=source_path, use_fused=use_fused, balance=balance, n=n_trials)
return score
if __name__ == "__main__":
#arguments = docopt(__doc__)
held_out_test = True
job_id = 0
params = {
'log_gamma': -1.69406367,
'log_C': -1.69406367
}
if held_out_test:
experiment(params=params, classifier_fn=rbfSVM, structure=structure, side=default_side, dataset=default_dataset,
folds=folds, source_path=source_path, use_fused=use_fused, balance=balance, n=n_trials, test=True)
else:
for side in sides:
for dataset in adni_datasets:
main(job_id, params, side, dataset)