diff --git a/code/bolsonaro/data/dataset_loader.py b/code/bolsonaro/data/dataset_loader.py index f7b6d92de841cff0571c48c069494d968c443103..5e6187a7b56bccb11bb8fc80dcce296b54df1d75 100644 --- a/code/bolsonaro/data/dataset_loader.py +++ b/code/bolsonaro/data/dataset_loader.py @@ -26,6 +26,10 @@ class DatasetLoader(object): DEFAULT_SUBSETS_USED = 'train,dev' DEFAULT_NORMALIZE_WEIGHTS = False + dataset_names = ['boston', 'iris', 'diabetes', 'digits', 'linnerud', 'wine', + 'breast_cancer', 'olivetti_faces', '20newsgroups_vectorized', 'lfw_people', + 'lfw_pairs', 'covtype', 'rcv1', 'california_housing'] + @staticmethod def load(dataset_parameters): name = dataset_parameters.name diff --git a/code/compute_hyperparameters.py b/code/compute_hyperparameters.py index 510fd9891f4f986e0ec7e10ea0bc72a18fcf53a6..06a451b2818039f682bf08a8538f19b68a14ba73 100644 --- a/code/compute_hyperparameters.py +++ b/code/compute_hyperparameters.py @@ -45,14 +45,12 @@ if __name__ == "__main__": 'min_samples_leaf': Integer(1, 1000), 'max_depth': Integer(1, 20), 'max_features': Categorical(['auto', 'sqrt', 'log2'], [0.5, 0.25, 0.25])} - DATASET_LIST = ['boston', 'iris', 'diabetes'] - # , 'digits', 'linnerud', 'wine'] parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('--cv', nargs='?', type=int, default=DEFAULT_CV, help='Specify the size of the cross-validation.') parser.add_argument('--n_iter', nargs='?', type=int, default=DEFAULT_N_ITER, help='Specify the number of iterations for the bayesian search.') parser.add_argument('--seed', nargs='?', type=int, default=None, help='Specify a seed instead of generate it randomly.') - parser.add_argument('--datasets', nargs='+', type=str, default=DATASET_LIST, help='Specify the dataset used by the estimator.') + parser.add_argument('--datasets', nargs='+', type=str, default=DatasetLoader.dataset_names, help='Specify the dataset used by the estimator.') parser.add_argument('--verbose', action='store_true', default=False, help='Print information during the bayesian search.') args = parser.parse_args()