Is it possible to reuse my CNN trained model over a new dataset with different number of classes?

Question

I had used a trained CNN model (VGG16) over a large dataset with 6 number of classes in FC layer it gave me a good accuracy ( for example over Testing data: loss=0.59, accuracy=0.829).

When I had applied the same model over a dataset with less samples and labels (4 classes) it reduced the accuracy.

Here my question is : is it possible to use model 1 over the 2nd dataset (bec I had saved the attained weights) or it is not possible due to the difference in classes number?

Also if I rerun my model 1 does the accuracy would be improved or no?

Answer 1

I think if the new test data (one with fewer samples and 4 classes) is from the same distribution as the original training data, the model should be applicable, you can use the pre-trained model.

Regarding the drop in accuracy I don't think it is because there are less number of classes (if the new test data is from same distribution as original train data). May be check if the images(or data) in the new test dataset is very different from original training data and old test dataset.

Answer 2

The accuracy will downgrade since the model was trained on a dataset with 6 classes but is being tested on 4 classes.

If you want a good accuracy for the dataset with 4 classes, first train it on the data of 4 classes and then test it on some test data with 4 classes.

Hope this is of help.