I created an image classification model using CNNs for 235 classes and I got 71% accuracy on the test set. My dataset contains some classes with more than 1000 images and others with 30 images. For example, in the classification report I can see that I have 98% accuracy for the classes that contains a lot of images but less than 20% accuracy for other classes with few images. I used data augmentation but it still not good. This influences the performance of my model, can anyone help me to improve it? Thank you

  • $\begingroup$ Try adding class weights Sample $\endgroup$
    – 10xAI
    Jul 5, 2021 at 16:31
  • $\begingroup$ @10xAI I'm using ImageDataGenerator().flow_from_directory in order to have my training batches and test data. Do you have any idea how to use my training data in order to use the fit_resample ? fit_resample requires X,Y as parameters which are arrays. thank you $\endgroup$
    – Lema Zaidi
    Jul 6, 2021 at 14:43
  • $\begingroup$ I never heard of this method fit_resample in keras. Could you please share the link? $\endgroup$
    – 10xAI
    Jul 8, 2021 at 16:48


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