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» Adaptation to Drifting Concepts
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MSR
2009
ACM
14 years 2 months ago
Tracking concept drift of software projects using defect prediction quality
Defect prediction is an important task in the mining of software repositories, but the quality of predictions varies strongly within and across software projects. In this paper we...
Jayalath Ekanayake, Jonas Tappolet, Harald Gall, A...
ICDM
2008
IEEE
145views Data Mining» more  ICDM 2008»
14 years 2 months ago
Paired Learners for Concept Drift
To cope with concept drift, we paired a stable online learner with a reactive one. A stable learner predicts based on all of its experience, whereas a reactive learner predicts ba...
Stephen H. Bach, Marcus A. Maloof
DEXA
2008
Springer
123views Database» more  DEXA 2008»
13 years 9 months ago
Evolutionary Clustering in Description Logics: Controlling Concept Formation and Drift in Ontologies
Abstract. We present a method based on clustering techniques to detect concept drift or novelty in a knowledge base expressed in Description Logics. The method exploits an effectiv...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
ESWS
2008
Springer
13 years 9 months ago
Conceptual Clustering and Its Application to Concept Drift and Novelty Detection
Abstract. The paper presents a clustering method which can be applied to populated ontologies for discovering interesting groupings of resources therein. The method exploits a simp...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
MCS
2009
Springer
14 years 6 days ago
Incremental Learning of Variable Rate Concept Drift
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
Ryan Elwell, Robi Polikar