from templates import make_suite as _make_suite
_benchmarks = [
{
'obj': 'GaussianProcess',
'spec': 'cobyla',
'init_params': {'optimizer': 'fmin_cobyla', 'random_state': 0},
'datasets': ('blobs',),
'statements': ('fit', 'predict')
},
{
'obj': 'GaussianProcess',
'spec': 'Welch',
'init_params': {'optimizer': 'Welch', 'random_state': 0},
'datasets': ('blobs',),
'statements': ('fit', 'predict')
},
]
suite = _make_suite(_benchmarks)
'statements': ('fit_unsup', 'transform_unsup')
},
{
'obj': 'FastICA',
'spec': 'parallel',
'init_params': {'n_components': 9, 'algorithm': 'parallel'},
'datasets': ('arcene', 'madelon'),
'statements': ('fit_unsup', 'transform_unsup')
},
{
'obj': 'NMF',
'init_params': {'n_components': 2},
'datasets': ('blobs',),
'statements': ('fit_unsup', 'transform_unsup', 'fit_transform')
},
{
'obj': 'MiniBatchDictionaryLearning',
'init_params': {'n_atoms': 50, 'n_iter': 300},
'datasets': ('blobs',),
'statements': ('fit_unsup', 'transform_unsup', 'fit_transform')
},
{
'obj': 'MiniBatchSparsePCA',
'init_params': {'n_components': 2},
'datasets': ('blobs',),
'statements': ('fit_unsup', 'fit_transform')
},
]
suite = _make_suite(_benchmarks)
'datasets': ('minimadelon', 'madelon'),
'statements': ('fit',)
},
{
'obj': 'SGDClassifier',
'init_params': {},
'datasets': ('madelon', 'newsgroups'),
'statements': ('fit', 'predict')
},
{
'obj': 'LogisticRegression',
'init_params': {'C': 1e5},
'datasets': ('arcene', 'madelon'),
'statements': ('fit', 'predict')
},
{
'obj': 'ARDRegression',
'init_params': {},
'datasets': ('minimadelon-oney', 'blobs'),
'statements': ('fit',)
},
{
'obj': 'BayesianRidge',
'init_params': {},
'datasets': ('arcene', 'madelon'),
'statements': ('fit',)
}
]
suite = _make_suite(config_arg_list=_benchmarks)
