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)