Active learning is a special case of machine learning in which the learning algorithm can interactively query the user (or some other information source) to label new data points with the desired output.In active learning, the algorithm actively selects a subset of examples from the pool of unlabeled data to label next. The basic belief behind the concept of active learning algorithms is that a machine learning algorithm may achieve higher accuracy with a smaller number of training labels if it is allowed to select the data it wants to learn from.