Question

我试图找到召回但发生输入错误

import pandas as pd
y_test = {'o1':  [0,1,0,1],'o2': [1,1,0,1],'o3':[0,0,1,1]}
y_test = pd.DataFrame (y_test)
y_pred = {'o1':  [1,1,0,1],'o2': [1,0,0,1],'o3':[1,0,1,1]}
y_pred = pd.DataFrame (y_pred)
y_pred = y_pred.to_numpy()


def precision(y_test, y_pred):
    i = set(y_test).intersection(y_pred)
    len1 = len(y_pred)
    if len1 == 0:
        return 0
    else:
        return len(i) / len1

print("recall of Binary Relevance Classifier: " + str(precision(y_test, y_pred)))

此代码显示错误：实际上，我尝试找到针对多标签分类的召回产品错误详情如下

TypeError                                 Traceback (most recent call last)
<ipython-input-41-8f3ca706a8e6> in <module>
16         return len(i) / len1
17 
---> 18 print("recall of Binary Relevance Classifier: " + str(precision(y_test, y_pred)))
<ipython-input-41-8f3ca706a8e6> in precision(y_test, y_pred)
 9 
10 def precision(y_test, y_pred):
---> 11     i = set(y_test).intersection(y_pred)
 12     len1 = len(y_pred)
 13     if len1 == 0:

TypeError: unhashable type: 'numpy.ndarray'

Answer 1

您的numpy数组y_test无法转换为集合（在第11行），因为该数组是二维的。

要将可迭代对象转换为集合，所有项目都必须是可哈希的。对于一维numpy数组来说很好，因为数字是可哈希的：

>>> array_1d = np.array([1, 2, 3])
>>> array_1d
array([1, 2, 3])
>>> set(array_1d)
{1, 2, 3}

但是对于二维数组，您会收到此错误，因为嵌套数组本身不可哈希：

>>> array_2d = np.array([[1,2,3], [1,2,3], [1,2,3]])
>>> array_2d
array([[1, 2, 3],
       [1, 2, 3],
       [1, 2, 3]])
>>> set(array_2d)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: unhashable type: 'numpy.ndarray'

在python中TypeError：无法散列的类型：'numpy.ndarray'

1 个答案: