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)
