Comments by Member 14869671 (Top 6 by date)

scores= model.evaluate(validation_generator,verbose=0)
print("aa:%.2f%%" % (scores[1]*100))



aa:96.81%

this is want i get when i compute the confusion matrix

Confusion Matrix
[[24 12 31 21 15 17]
[28 21 30 14 17 10]
[19 21 29 23 17 11]
[18 28 30 16 13 15]
[13 30 28 17 20 12]
[21 22 30 20 14 13]]
Classification Report
precision recall f1-score support

1 0.20 0.20 0.20 120
2 0.16 0.17 0.17 120
3 0.16 0.24 0.19 120
4 0.14 0.13 0.14 120
5 0.21 0.17 0.19 120
6 0.17 0.11 0.13 120

accuracy 0.17 720
macro avg 0.17 0.17 0.17 720
weighted avg 0.17 0.17 0.17 720

i means the the prediction