Learning under Concept Drift: an Overview
–arXiv.org Artificial Intelligence
Concept drift refers to a non stationary learning problem over time. The training and the application data often mismatch in real life problems. In this report we present a context of concept drift problem 1. We focus on the issues relevant to adaptive training set formation. We present the framework and terminology, and formulate a global picture of concept drift learners design. We start with formalizing the framework for the concept drifting data in Section 1. In Section 2 we discuss the adaptivity mechanisms of the concept drift learners. In Section 3 we overview the principle mechanisms of concept drift learners. In this chapter we give a general picture of the available algorithms and categorize them based on their properties. Section 5 discusses the related research fields and Section 5 groups and presents major concept drift applications. This report is intended to give a bird's view of concept drift research field, provide a context of the research and position it within broad spectrum of research fields and applications.
arXiv.org Artificial Intelligence
Oct-22-2010
- Country:
- North America > United States > Wisconsin (0.14)
- Industry:
- Banking & Finance (1.00)
- Education (1.00)
- Health & Medicine > Pharmaceuticals & Biotechnology (1.00)
- Information Technology > Security & Privacy (1.00)
- Law Enforcement & Public Safety (1.00)
- Leisure & Entertainment > Sports
- Soccer (0.46)
- Telecommunications (0.93)
- Transportation (1.00)
- Technology: