def test_from_provided():
data_file = './tests/data.txt'
data = Reader.read_uir_triplets(data_file)
try:
BaseMethod.from_provided(train_data=None, test_data=None)
except ValueError:
assert True
try:
BaseMethod.from_provided(train_data=data, test_data=None)
except ValueError:
assert True
bm = BaseMethod.from_provided(train_data=data, test_data=data)
assert bm.total_users == 10
assert bm.total_items == 10
train_path = DownloadItem(
url='http://files.grouplens.org/datasets/movielens/ml-100k/u1.base',
relative_path='u1.base',
sub_dir='datasets/ml_100k').download_if_needed(True)
test_path = DownloadItem(
url='http://files.grouplens.org/datasets/movielens/ml-100k/u1.test',
relative_path='u1.test',
sub_dir='datasets/ml_100k').download_if_needed(True)
# Load data using Reader
train_data = Reader.read_uir_triplets(train_path)
test_data = Reader.read_uir_triplets(test_path)
# Construct base evaluation method with given data
eval_method = BaseMethod.from_provided(train_data=train_data,
test_data=test_data,
exclude_unknowns=False,
verbose=True)
# Model
mf = cn.models.MF(k=10,
max_iter=25,
learning_rate=0.01,
lambda_reg=0.02,
use_bias=True,
early_stop=True,
verbose=True)
# Metrics
mae = cn.metrics.MAE()
rmse = cn.metrics.RMSE()
