Getting the warning UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples when I calculate the confusion matrix of my classification model through the scikit-learn's confusion_matrix function. I have re-confirmed that the class 1 contains images for training, validation, and test purposes just like the other classes. How can I fix this issue?
Here is the output:
[[115   0  17  66  96 183  18]
 [ 11   0   2  10   8  21   2]
 [ 42   0  35  68 102 172  93]
 [ 15   0   9 690  63 102  19]
 [ 12   0   7  86 315 186  13]
 [ 27   0  13  84 151 317  15]
 [  8   0  18  44  46  30 254]]

And here is my classification report:
              precision    recall  f1-score   support

           0      0.500     0.232     0.317       495
           1      0.000     0.000     0.000        54
           2      0.347     0.068     0.114       512
           3      0.658     0.768     0.709       898
           4      0.403     0.509     0.450       619
           5      0.314     0.522     0.392       607
           6      0.614     0.635     0.624       400

    accuracy                          0.481      3585
   macro avg      0.405     0.391     0.372      3585
weighted avg      0.475     0.481     0.451      3585