Learning model trees from evolving data streams

Abstract

The problem of real-time extraction of meaningful patterns from timechanging data streams is of increasing importance for the machine learning and data mining communities. Regression in time-changing data streams is a relatively unexplored topic, despite the apparent applications. This paper proposes an efficient and incremental stream mining algorithm which is able to learn regression and model trees © 2010 The Author(s).