Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC

  • Gregory Ditzler
  • Michael D. Muhlbaier
  • Robi Polikar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5997)

Abstract

We have previously described an incremental learning algorithm, Learn + + .NC, for learning from new datasets that may include new concept classes without accessing previously seen data. We now propose an extension, Learn + + .UDNC, that allows the algorithm to incrementally learn new concept classes from unbalanced datasets. We describe the algorithm in detail, and provide some experimental results on two separate representative scenarios (on synthetic as well as real world data) along with comparisons to other approaches for incremental and/or unbalanced dataset approaches.

Keywords

Incremental Learning Ensembles of Classifiers Learn++ Unbalanced Data 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Gregory Ditzler
    • 1
  • Michael D. Muhlbaier
    • 1
  • Robi Polikar
    • 1
  1. 1.Signal Processing and Pattern Recognition Laboratory Electrical and Computer EngineeringRowan UniversityGlassboroUSA

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