First node, second node and methods performed thereby for handling data augmentation

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Abstract: A method performed by a first node for handling data augmentation. The first node divides each epoch in an original dataset having an input space, into a set of batches. The first node generates a set of subsets of samples by selecting, within each batch from every set of batches, a respective plurality of subsets. The first node determines, using machine learning, a fourth set of clusters of data using the third set. The first node selects a fifth set of clusters from the fourth set based on a relevance criterion. The first node generates samples in each cluster of the fifth set, and refrains from generating samples in clusters of the fourth set excluded from the fifth set. The first node then generates a sixth set of augmented samples in the input space of the original dataset, by using the generated samples and applying a reverse projection approach.

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