def main_test(run_exp=False):
params_gridsearch = {
'rf_dim': [4000],
'regular_param': [4.7971777603588588e-05],
'gamma': [0.00390625],
'oracle': ['budget'],
'core_max': [400],
'loss_func': ['hinge'],
'num_epochs': [2],
'freq_update_full_model': [5000]
}
attribute_names = (
'gamma', 'regular_param', 'learning_rate_scale', 'num_epochs', 'cache_size',
'oracle', 'loss_func', 'core_max', 'coverage_radius', 'model_name', 'batch_size')
main_func(
create_obj_func,
choice_default=choice_default,
dataset_default='airline.2008',
params_gridsearch=params_gridsearch,
attribute_names=attribute_names,
num_workers=4,
file_config=None,
run_exp=run_exp,
freq_predict_display=10,
)
def main_test(run_exp=False):
params_gridsearch = {
'rf_dim': [4000],
'regular_param': [1e-7],
'gamma': [1.0],
'oracle': ['coverage'],
'coverage_radius': [40],
'loss_func': ['logistic'],
'num_epochs': [2],
'freq_update_full_model': [100]
}
attribute_names = ('gamma', 'regular_param', 'learning_rate_scale',
'num_epochs', 'cache_size', 'oracle', 'loss_func',
'core_max', 'coverage_radius', 'model_name',
'batch_size')
main_func(
create_obj_func,
choice_default=choice_default,
dataset_default='w8a',
params_gridsearch=params_gridsearch,
attribute_names=attribute_names,
num_workers=4,
file_config=None,
run_exp=run_exp,
freq_predict_display=10,
)
def main_test(run_exp=False):
params_gridsearch = {
'rf_dim': [1600],
'regular_param': [1.07570927967064E-07],
'gamma': [4.0],
'oracle': ['budget'],
'core_max': [400],
'loss_func': ['hinge'],
}
attribute_names = ('gamma', 'regular_param', 'learning_rate_scale',
'num_epochs', 'cache_size', 'oracle', 'loss_func',
'core_max', 'coverage_radius', 'model_name',
'batch_size')
main_func(
create_obj_func,
choice_default=choice_default,
dataset_default='covtype',
params_gridsearch=params_gridsearch,
attribute_names=attribute_names,
num_workers=4,
file_config=None,
run_exp=run_exp,
freq_predict_display=10,
)
def main_test(run_exp=False):
params_gridsearch = {
'regular_param': [3.7747016475817751e-07],
}
attribute_names = ('gamma', 'regular_param', 'learning_rate_scale',
'num_epochs', 'cache_size', 'oracle', 'loss_func',
'core_max', 'coverage_radius', 'model_name',
'batch_size')
main_func(create_obj_func,
choice_default=choice_default,
dataset_default='svmguide1',
params_gridsearch=params_gridsearch,
attribute_names=attribute_names,
num_workers=4,
file_config=None,
run_exp=run_exp,
freq_predict_display=10,
run_online=True)
def main_test(run_exp=False):
params_gridsearch = {
'regular_param': [1.0540672407201184e-08],
'gamma': [16.0],
'loss_func': ['logistic'],
'oracle': ['budget'],
}
attribute_names = ('gamma', 'regular_param', 'learning_rate_scale',
'num_epochs', 'cache_size', 'oracle', 'loss_func',
'core_max', 'coverage_radius', 'model_name',
'batch_size')
main_func(create_obj_func,
choice_default=choice_default,
dataset_default='airline',
params_gridsearch=params_gridsearch,
attribute_names=attribute_names,
num_workers=4,
file_config=None,
run_exp=run_exp,
freq_predict_display=10,
run_online=True)
def main_test(run_exp=False):
params_gridsearch = {
'regular_param': [0.0030922355896989902],
'gamma': [0.00390625],
'loss_func': ['hinge'],
'oracle': ['coverage'],
}
attribute_names = ('gamma', 'regular_param', 'learning_rate_scale',
'num_epochs', 'cache_size', 'oracle', 'loss_func',
'core_max', 'coverage_radius', 'model_name',
'batch_size')
main_func(create_obj_func,
choice_default=choice_default,
dataset_default='cod-rna',
params_gridsearch=params_gridsearch,
attribute_names=attribute_names,
num_workers=4,
file_config=None,
run_exp=run_exp,
freq_predict_display=10,
run_online=True)
