def compute_features_from_aes_for_train_set(): train_x, train_y = SupervisedLoader.load('../data') config = load_configuration('../config/caes.json') scaes = StackedAutoencoders(config, warm_start=True) train_x = scaes.get_features(train_x) np.save('../data/features.npy', train_x) np.save('../data/hazards.npy', train_y)
def compute_features_from_aes_for_test_set(): test_x, ids = TestSetLoader.load('../data') config = load_configuration('../config/caes.json') scaes = StackedAutoencoders(config, warm_start=True) test_x = scaes.get_features(test_x) np.save('../data/test_x.npy', test_x) np.save('../data/test_ids.npy', ids)
def train_stacked_aes(): mini_batch_size = 128 generator = UnsupervisedLoader('../data', dump_parameters=True) config = load_configuration('../config/caes.json') scaes = StackedAutoencoders(config, mini_batch_size=mini_batch_size) scaes.train(generator)