Exploring query strategies scenarios
Active learning can be implemented in different ways, depending on the nature of the unlabeled data and how the queries are performed. There are three main scenarios to consider when implementing active learning:
- Membership query synthesis
- Stream-based selective sampling
- Pool-based sampling
These scenarios offer different ways to optimize and improve the active learning process. Understanding these scenarios can help you make informed decisions and choose the most suitable approach for your specific needs. In this section, we will explore each of these scenarios.
Membership query synthesis
In membership query synthesis, the active learner has the ability to create its own unlabeled data points in order to improve its training. This is done by generating new data points from scratch and then requesting the oracle for labels, as depicted in Figure 1.2. By incorporating these newly labeled data points into its training...
