大家好，我不知道为什么这个函数不能按预期工作。如有任何指导，我们将不胜感激。我得到错误：
ValueError: too many values to unpack (expected 2)
编写一个函数，将一个二维numpy数组作为输入，并以(X_train, y_train), (X_test, y_test)的形式返回四个变量，其中(X_train, y_train)是训练集的特征+响应，(X-test, y_test)是测试集的特征-响应。
功能规范：
- 应采用二维numpy
array作为输入 - 应该拆分数组，使得X是年份，y是相应的总体
- 应返回两个形式为
(X_train, y_train), (X_test, y_test)的tuples - 应将sklearn的train_testrongplit函数与
test_size = 0.2和random_state = 42一起使用
Numpy数组输入：
array([[ 1960, 54211],
[ 1961, 55438],
[ 1962, 56225],
[ 1963, 56695],
[ 1964, 57032],
[ 1965, 57360],
[ 1966, 57715],
[ 1967, 58055],
[ 1968, 58386],
[ 1969, 58726],
[ 1970, 59063],
[ 1971, 59440]...
我的功能：
def feature_response_split(arr):
X, y = np.split(arr, 2, axis=1)
(X_train, y_train), (X_test, y_test) = train_test_split(X, y, test_size = 0.2, random_state = 42)
return (X_train, y_train), (X_test, y_test)
输入代码：(不可更改(
data = get_year_pop('Aruba')
(X_train, y_train), (X_test, y_test) = feature_response_split(data)
预期输出：
X_train == array([1996, 1991, 1968, 1977, 1966, 1964, 2001, 1979, 1990, 2009, 2010,
2014, 1975, 1969, 1987, 1986, 1976, 1984, 1993, 2015, 2000, 1971,
1992, 2016, 2003, 1989, 2013, 1961, 1981, 1962, 2005, 1999, 1995,
1983, 2007, 1970, 1982, 1978, 2017, 1980, 1967, 2002, 1974, 1988,
2011, 1998])
y_train == array([ 83200, 64622, 58386, 60366, 57715, 57032, 92898, 59980,
62149, 101453, 101669, 103795, 60657, 58726, 61833, 62644,
60586, 62836, 72504, 104341, 90853, 59440, 68235, 104822,
97017, 61032, 103187, 55438, 60567, 56225, 100031, 89005,
80324, 62201, 101220, 59063, 61345, 60103, 105264, 60096,
58055, 94992, 60528, 61079, 102053, 87277])
X_test == array([1960, 1965, 1994, 1973, 2004, 2012, 1997, 1985, 2006, 1972, 2008,
1963])
y_test == array([ 54211, 57360, 76700, 60243, 98737, 102577, 85451, 63026,
100832, 59840, 101353, 56695])
这是不正确的：
(X_train, y_train), (X_test, y_test) = train_test_split(X, y, ...)
根据文件，它应该是
X_train, X_test, y_train, y_test = train_test_split(X, y, ...)