TypeError:不支持的操作数类型 - :' numpy.ndarray'和' numpy.ndarray'

时间:2013-05-02 04:32:07

标签: python python-2.7 numpy scipy scikit-learn

我正在尝试使用原始值y_train_actual从我的sci-kit学习模型计算预测salaries的均方误差。

问题:但是对于mean_squared_error(y_train_actual, salaries),我收到错误TypeError: unsupported operand type(s) for -: 'numpy.ndarray' and 'numpy.ndarray'。使用list(salaries)代替salaries作为第二个参数会产生相同的错误。

mean_squared_error(y_train_actual, y_valid_actual)我收到错误Found array with dim 40663. Expected 244768

如何转换为sklearn.netrucs.mean_squared_error()的正确数组类型?

代码

from sklearn.metrics import mean_squared_error

y_train_actual = [ np.exp(float(row)) for row in y_train ]
print mean_squared_error(y_train_actual, salaries)

错误

TypeError                                 Traceback (most recent call last)
<ipython-input-144-b6d4557ba9c5> in <module>()
      3 y_valid_actual = [ np.exp(float(row)) for row in y_valid ]
      4 
----> 5 print mean_squared_error(y_train_actual, salaries)
      6 print mean_squared_error(y_train_actual, y_valid_actual)

C:\Python27\lib\site-packages\sklearn\metrics\metrics.pyc in mean_squared_error(y_true, y_pred)
   1462     """
   1463     y_true, y_pred = check_arrays(y_true, y_pred)
-> 1464     return np.mean((y_pred - y_true) ** 2)
   1465 
   1466 

TypeError: unsupported operand type(s) for -: 'numpy.ndarray' and 'numpy.ndarray'

代码

y_train_actual = [ np.exp(float(row)) for row in y_train ]
y_valid_actual = [ np.exp(float(row)) for row in y_valid ]

print mean_squared_error(y_train_actual, y_valid_actual)

错误

ValueError                                Traceback (most recent call last)
<ipython-input-146-7fcd0367c6f1> in <module>()
      4 
      5 #print mean_squared_error(y_train_actual, salaries)
----> 6 print mean_squared_error(y_train_actual, y_valid_actual)

C:\Python27\lib\site-packages\sklearn\metrics\metrics.pyc in mean_squared_error(y_true, y_pred)
   1461 
   1462     """
-> 1463     y_true, y_pred = check_arrays(y_true, y_pred)
   1464     return np.mean((y_pred - y_true) ** 2)
   1465 

C:\Python27\lib\site-packages\sklearn\utils\validation.pyc in check_arrays(*arrays, **options)
    191         if size != n_samples:
    192             raise ValueError("Found array with dim %d. Expected %d"
--> 193                              % (size, n_samples))
    194 
    195         if not allow_lists or hasattr(array, "shape"):

ValueError: Found array with dim 40663. Expected 244768

代码

print type(y_train)
print type(y_train_actual)
print type(salaries)

结果

<type 'list'>
<type 'list'>
<type 'tuple'>

打印y_train [:10]

[10.126631103850338, 10.308952660644293, 10.308952660644293, 10.221941283654663, 10.126631103850338, 10.126631103850338, 11.225243392518447, 9.9987977323404529, 10.043249494911286, 11.350406535472453]

打印工资[:10]

('25000', '30000', '30000', '27500', '25000', '25000', '75000', '22000', '23000', '85000')

打印列表(工资)[:10]

['25000', '30000', '30000', '27500', '25000', '25000', '75000', '22000', '23000', '85000']

打印len(y_train)

244768

打印len(薪水)

244768

1 个答案:

答案 0 :(得分:9)

TypeError问题源于薪水是字符串列表,而y_train_actual是浮点列表。那些不能被减去。

对于第二个错误,您应确保两个数组的大小相同,否则无法减去它们。