Publication | Open Access
Learning under Concept Drift: an Overview
235
Citations
107
References
2010
Year
Artificial IntelligenceIncremental LearningEngineeringMachine LearningShift DetectionText MiningConcept Drift LearnersConcept DriftInformation RetrievalData ScienceData MiningPattern RecognitionAdaptivity MechanismsGlobal PicturePredictive AnalyticsKnowledge DiscoveryLearning AnalyticsComputer ScienceData Stream MiningLearning Classifier System
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.
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