Core support extraction for learning from initially labeled nonstationary environments using COMPOSE

@article{Capo2014CoreSE,
  title={Core support extraction for learning from initially labeled nonstationary environments using COMPOSE},
  author={Robert Capo and Anthony Sanchez and Robi Polikar},
  journal={2014 International Joint Conference on Neural Networks (IJCNN)},
  year={2014},
  pages={602-608}
}
Learning in nonstationary environments, also called concept drift, requires an algorithm to track and learn from streaming data, drawn from a nonstationary (drifting) distribution. When data arrive continuously, a concept drift algorithm is required to maintain an up-to-date hypothesis that evolves with the changing environment. A more difficult problem that has received less attention, however, is learning from so-called initially labeled nonstationary environments, where the the environment… CONTINUE READING

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