A study on Incremental Learning for Boosting Classifier

Abstract

We propose an incremental learning model for boosting classifier system whose composite classifier can learn incrementally without serious forgetting. In this system, a designated number of composite classifiers are constructed in advance, and then every classifier is sequentially trained every time when a new training sample is given.