deep learning - python got result and here is keyerror: 1

Question

 #compute ROC curve and ROC area for each class
        fpr= dict()
        tpr= dict()
        roc_auc = dict()
        y_test= to_categorical(Y_test, num_classes)
        y_test=np.array(y_test)
        pred= np. array(predictions)
        n_classes= num_classes
        lw=2 #float values in point
    
    
    for i in range(n_classes):
        fpr[i], tpr[i], _ = roc_curve(y_test[:, i], pred[:, i])
        roc_auc[i] = auc(fpr[i], tpr[i])
        
    #compute micro-average ROC curve and ROC area
        fpr["micro"], tpr["micro"], _ = roc_curve(y_test.ravel(), pred.ravel())
        roc_auc["micro"]= auc(fpr["micro"], tpr["micro"])
        
    #compute macro-average ROC curve and ROC area   
    # first  aggregate  all false posivte rates
        
        all_fpr = np.unique(np.concatenate([fpr[i] for i in range (n_classes)]))   
      
    
    # Then interpolate all ROC curves at this points
        mean_tpr= np.zeros_like(all_fpr)
        for i in range (n_classes):
            mean_tpr += interp(all_fpr, fpr[i],tpr[i])
        
    #finally average it and compute auc
        mean_tpr /= n_classes
        
        fpr["macro"]= all_fpr
        tpr["macro"]=mean_tpr
        roc_auc["macro"]= auc(fpr["macro"],tpr["macro"])
    
    #plot all ROC 
        plt.figure()............

I failed to find out the reason of this error, #PROBLEM File "", line 241, in all_fpr = np.unique(np.concatenate([fpr[i] for i in range (n_classes)])) KeyError: 1 i tried alot but failed to fix it ...someone plz help me here is code

question from:https://stackoverflow.com/questions/65943704/python-got-result-and-here-is-keyerror-1

Answer 1

The error suggests that your dictionary fpr does not have an entry with the key 1, you might want to look into your conditions again to prevent this.

Here is a small example of the error

>>> d={0: 'hi'}
>>> print(d[0])
hi
>>> print(d[1])
Traceback (most recent call last):
  File "<pyshell#2>", line 1, in <module>
    print(d[1])
KeyError: 1
>>>