How do I increase the size of an (almost) balanced dataset? I am trying to add more data points in my (almost) balanced dataset for training my neural network. I have come across techniques such as SMOTE or Random Over Sampling, but they work best for imbalanced data (as they balance the dataset). How can I do this and is it even worth it?
P.S. I know copying the same data points and appending them at the end doesn't add much value, but can we do it, and can it help to increase the prediction accuracy?
Random over sampling creates duplicates of existing examples, so applying this to your training data would be the same as increasing the weight of the oversampled examples. If it's done to all of the examples uniformly then the effects will probably cancel out. SMOTE, on the other hand, creates synthetic examples that are linear combinations of existing examples. Thus it can be thought of as a type of data augmentation, and in some situations this might improve your model's predictions.