Related fields

As we know, one-shot learning is a sub-field of ML. There are different relevant solutions that are very similar to the one-shot learning approach, yet slightly different in their solution approach. Such problems can be solved by using one-shot learning algorithms as well. Let's go through each of the relevant fields of ML and observe how similar they are to the one-shot learning problem:

• Semi-supervised learning
• Imbalanced learning
• Meta-learning
• Transfer learning

Semi-supervised learning

Suppose we have 10,000 data points where only 20,000 are labeled and 80,000 are unlabeled. In such cases, we would employ semi-supervised learning. In semi-supervised learning, we use unlabeled data to gain more of an...