# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Example for Social Bayesian Personalized Ranking with Epinions dataset"""
import cornac
from cornac.data import Reader, GraphModule
from cornac.datasets import epinions
from cornac.eval_methods import RatioSplit
ratio_split = RatioSplit(data=epinions.load_data(Reader(bin_threshold=4.0)),
test_size=0.1,
rating_threshold=0.5,
exclude_unknowns=True,
verbose=True,
user_graph=GraphModule(data=epinions.load_trust()))
sbpr = cornac.models.SBPR(k=10,
max_iter=50,
learning_rate=0.001,
lambda_u=0.015,
lambda_v=0.025,
lambda_b=0.01,
verbose=True)
rec_10 = cornac.metrics.Recall(k=10)
def test_load_data(self):
# only run data download tests 20% of the time to speed up frequent testing
random.seed(time.time())
if random.random() > 0.8:
self.assertEqual(len(epinions.load_data()), 664824)