DatasetAutoFolds对象在python上没有属性'global_mean'

我很惊讶地执行交叉验证

def cross_v(data, folds=5):
    algorithms = (SVD, KNNBasic, KNNWithMeans, NormalPredictor)
    measures = ['RMSE', 'MAE']

for a in algorithms:
    data.split(folds);
    algo = a();
    algo.fit(data)

我这样调用函数

data = Dataset.load_builtin('ml-100k')
multiple_cv(data)

我得到这个错误

Traceback (most recent call last):
  File "/home/user/PycharmProjects/pac1/prueba.py", line 30, in 
    multiple_cv(data)
  File "/home/user/PycharmProjects/pac1/prueba.py", line 19, in multiple_cv
    algo.fit(data)
  File "surprise/prediction_algorithms/matrix_factorization.pyx", line 155, in surprise.prediction_algorithms.matrix_factorization.SVD.fit
  File "surprise/prediction_algorithms/matrix_factorization.pyx", line 204, in surprise.prediction_algorithms.matrix_factorization.SVD.sgd
AttributeError: 'DatasetAutoFolds' object has no attribute 'global_mean'

我错过了什么？

根据docs，fit方法的输入必须是Trainset，它与您要使用的Dataset不同。您可以使用此处提到的split方法的输出将数据集拆分为Trainset（和Testset）。

在您的示例中

data = Dataset.load_builtin('ml-100k')
trainset = data.build_full_trainset()

然后，您可以使用

algo.fit(trainset)

这样获得的训练集和测试集可以分别用作拟合和测试功能的输入。