活动识别项目中绘制混淆矩阵时的值误差

问题描述

尝试在人类活动识别上绘制混乱矩阵，一切正常，接受混乱矩阵。我无法打印混乱矩阵。

cm = confusion_matrix(y_test.values,y_pred)
plot_confusion_matrix(cm,np.unique(y_pred))

结果：

ValueError                                Traceback (most recent call last)
<ipython-input-29-7fc4511c54b7> in <module>
----> 1 cm = confusion_matrix(y_test.values,y_pred)
      2 plot_confusion_matrix(cm,np.unique(y_pred))  # plotting confusion matrix

~\anaconda3\lib\site-packages\sklearn\utils\validation.py in inner_f(*args,**kwargs)
     71                           FutureWarning)
     72         kwargs.update({k: arg for k,arg in zip(sig.parameters,args)})
---> 73         return f(**kwargs)
     74     return inner_f
     75 

~\anaconda3\lib\site-packages\sklearn\metrics\_classification.py in confusion_matrix(y_true,y_pred,labels,sample_weight,normalize)
    274 
    275     """
--> 276     y_type,y_true,y_pred = _check_targets(y_true,y_pred)
    277     if y_type not in ("binary","multiclass"):
    278         raise ValueError("%s is not supported" % y_type)

~\anaconda3\lib\site-packages\sklearn\metrics\_classification.py in _check_targets(y_true,y_pred)
     79     y_pred : array or indicator matrix
     80     """
---> 81     check_consistent_length(y_true,y_pred)
     82     type_true = type_of_target(y_true)
     83     type_pred = type_of_target(y_pred)

~\anaconda3\lib\site-packages\sklearn\utils\validation.py in check_consistent_length(*arrays)
    254     uniques = np.unique(lengths)
    255     if len(uniques) > 1:
--> 256         raise ValueError("Found input variables with inconsistent numbers of"
    257                          " samples: %r" % [int(l) for l in lengths])
    258 

ValueError: Found input variables with inconsistent numbers of samples: [2947,2937]

解决方法

y_test.values和y_pred的长度不同，一个包含2947个条目，另一个包含2937