Learn++: an incremental learning algorithm based on psycho-physiological models of learning

An incremental learning algorithm, Learn++, which allows supervised classification algorithms to learn from new data without forgetting previously acquired knowledge, is introduced. Learn++ is based on generating multiple classifiers using strategically chosen distributions of the training data and combining these classifiers through weighted majority voting. Learn++ shares various notions with psycho-physiological models of learning. The Learn++ algorithm, simulation results, and how the algorithm is related to various concepts in psycho-physiological learning models are discussed. The algorithm was tested on a variety of real world and synthetic datasets. Two sets of results are presented for optical handwritten digit recognition and gas sensing.