小编Xce*_*ior的帖子

我正在对每个变量进行神经网络编码，当我要拟合模型时，会出现错误。

indices[201] = [0,8] is out of order. Many sparse ops require sorted indices.
    Use `tf.sparse.reorder` to create a correctly ordered copy.

 [Op:SerializeManySparse]

我不知道如何解决它。我可以在这里打印一些代码，如果你想要更多，我仍然可以打印它

def process_atributes(df, train, test):

    continuas = ['Trip_Duration']
    cs = MinMaxScaler()
    trainCont = cs.fit_transform(train[continuas])
    testCont = cs.transform(test[continuas])

    discretas = ['Start_Station_Name', 'End_Station_Name', 'User_Type', 'Genero', 'Hora_inicio']
    ohe = OneHotEncoder()
    ohe.fit(train[discretas])

    trainDisc = ohe.transform(train[discretas])
    testDisc = ohe.transform(test[discretas])

    trainX = sc.sparse.hstack((trainDisc, trainCont))
    testX = sc.sparse.hstack((testDisc, testCont))
    return (trainX, testX)

def prepare_targets(df, train, test):

    labeled_col = ['RangoEdad']

    le = LabelEncoder()
    le.fit(train[labeled_col].values.ravel())
    trainY …