Computer Engineering Commons^™

Ensemble Learning For Data Stream Analysis: A Survey, Bartosz Krawczyk, Leandro L. Minku, João Gama, Jerzy Stefanowski, Michał Wozniak

Computer Science Publications

In many applications of information systems learning algorithms have to act in dynamic environments where data are collected in the form of transient data streams. Compared to static data mining, processing streams imposes new computational requirements for algorithms to incrementally process incoming examples while using limited memory and time. Furthermore, due to the non-stationary characteristics of streaming data, prediction models are often also required to adapt to concept drifts. Out of several new proposed stream algorithms, ensembles play an important role, in particular for non-stationary environments. This paper surveys research on ensembles for data stream classification as well as regression …