Is there any difference between keras and scikit-learn depending on the calculation method of accuracy?
Asked 1 months ago, Updated 1 months ago, 4 views
I am currently using Keras' CNN for multi-label image classification.
Also, we reconfirmed the accuracy using various evaluation methods (Recall, Precision, F1 score, Accuracy) for scikit-learn as well as keras accuracies.
As a result, the Accuracy calculated in keras represents approximately 90%, while the scikit-learn shows only about 60%.
I don't know why this is, so please tell me who it is.
Is the calculation of keras strange?
Is there a difference in calculation of accuracies between keras and scikit-learn?
Thank you for your hard work.
Calculating keras and scikit-learn accuracies
I imagine that is the same.
"As a result, the Accuracy calculated in keras represents about 90 percent, but all scikit-learns are around 60 percent." I think it is possible.
If you show me exactly what the multi-label image classification is, the contents of keras, the specific processing of scikit-learn, etc., I might get an answer.
Regarding keras and scikit-learn, why don't you check the degree of Accuracy in the articles on the Internet?