CNN features for classification

Question

I am new to deep learning and I hope you guys can help me. The following site uses CNN features for multi-class classification: https://www.mathworks.com/help/deeplearning/examples/feature-extraction-using-alexnet.html

This example extracts features from fully connected layer and the extracted features are fed to ECOC classifier.

In this example, regarding to the whole dataset, there are total 15 samples in each category and in the training dataset, there are 11 samples in each category.

My question are related to the dataset size: If I want to use cnn features for ECOC classification as above example, it must be required to have the number of samples in each category the same? If so, would you like to explain why? If not, would you like to show the reference papers which have used different numbers?

Thank you.

Answer 1

You may want to have a balanced dataset to prevent your model from learning a wrong probability distribution. If a category represents 95% of your dataset, a model that classifies everything as part of that category, will have an accuracy of 95%.