cv.py

# Implementação baseada em
# https://github.com/NicolasHug/Surprise/blob/master/examples/benchmark.py
set_cell_seed(MY_SEED)

# Os algortimos para verificar
classes = (SVD, BaselineOnly)

kf = KFold(random_state=MY_SEED)  # certifica que as dobras serão as mesmas

table = []
for klass in classes:
    start = time.time()
    out = cross_validate(klass(), data, ['rmse', 'mae'], kf, n_jobs=-1)
    cv_time = str(datetime.timedelta(seconds=int(time.time() - start)))
    mean_rmse = '{:.3f}'.format(np.mean(out['test_rmse']))
    mean_mae = '{:.3f}'.format(np.mean(out['test_mae']))

    new_line = [klass.__name__, mean_rmse, mean_mae, cv_time]
    table.append(new_line)

header = ['Algoritmo',
          'RMSE',
          'MAE',
          'Tempo'
          ]
pd.DataFrame(table, columns=header)