CNN With unbalanced Data
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I have a question regarding CNN in MATLAB
I have a dataset with imbalanced classes. 70 for A 20 for B and 10 for C. How can I reduce the effect of this imbalance during training. The input images are binary images
When performing a leave-one-out scheme, the prediction is mostly going to be A every time.
The network archetecture am using is the exact same as AlexNet network
image_size = 512;
layers = [
imageInputLayer([image_size image_size 1],'Normalization','none')
options = trainingOptions('sgdm',...
My main question is how to make the network predicting the other two classes as well instead of just shooting for A because it is the highest amount of data. Is there a command to use or something wrong with the network?
I do not prefer data augmentation for the dataset am using as the shape and size are important factors.
Greg Heath on 22 Jun 2020
Although you do not prefer data augmentation, duplication of the smaller dataset examples is probably the quickest and most reliable way to proceed.
Thank you for formally accepting my answer.