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)