Understanding active machine learning systems
Active machine learning (active ML) is a powerful approach that seeks to create predictive models with remarkable accuracy, all while minimizing the number of labeled training examples required. This is achieved by employing a clever strategy that involves selectively choosing the most informative data points to be labeled by a knowledgeable oracle, such as a human annotator. By doing so, active learning enables models to extract the necessary knowledge they need from a relatively small amount of data.
Now, let’s explore some definitions and the fundamental concepts that form the foundation of active ML.
Definition
Active learning can be defined as a dynamic and iterative approach to machine learning, where the algorithm intelligently engages with an oracle to label new data points. An oracle is a source that provides labels for data points queried by the active learner. The oracle acts as a teacher, guiding the model by...
