You will be shown an excerpt from a computer science scientific research paper, followed by a question about the paper. Please answer the question. Do not include any text in your response other than the answer.

Context: Besides few-shot learning, a related task is the ability to learn from a mixture oflabeled and unlabeled examples — semi-supervised learning, as wellas active learning, in which the learner has the option to request those missing labelsthat will be most helpful for the prediction task.Our graph-based architecture is naturally extended to these setups withminimal changes in the training design.We validate experimentally the model on few-shot image classification, matchingstate-of-the-art performance with considerably fewer parameters,and demonstrate applications to semi-supervised and active learning setups.

Question: What does Active learning means?
Active learning is training strategy which uses both labeld and unlabeld data in training as well as semi-supervised learning.