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Evolving classification function Source: en.wikipedia.org/wiki/Evolving_classification_function

Evolving classification functions (ECF), evolving classifier functions or evolving classifiers are used for classifying and clustering in the field of machine learning and artificial intelligence, typically employed for data stream mining tasks in dynamic and changing environments.


See also

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  • Supervised Classification on Data Streams [1]
  • Evolving fuzzy rule-based Classifier (eClass [2])
  • Evolving Takagi-Sugeno fuzzy systems (eTS [3])
  • Evolving All-Pairs (ensembled) classifiers (EFC-AP [4])
  • Evolving Connectionist Systems (ECOS)
Dynamic Evolving Neuro-Fuzzy Inference Systems (DENFIS)
Evolving Fuzzy Neural Networks (EFuNN)
Evolving Self-Organising Maps

References

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  1. ^ Lemaire, Vincent; Salperwyck, Christophe; Bondu, Alexis (2015). "A Survey on Supervised Classification on Data Streams". Business Intelligence. Lecture Notes in Business Information Processing. Vol. 205. pp. 88–125. doi:10.1007/978-3-319-17551-5_4. ISBN 978-3-319-17550-8. S2CID 26990770.
  2. ^ Angelov, Plamen (2008). "Evolving fuzzy systems". Scholarpedia. 3 (2): 6274. Bibcode:2008SchpJ...3.6274A. doi:10.4249/scholarpedia.6274.
  3. ^ Angelov, Plamen (2008). "Evolving fuzzy systems". Scholarpedia. 3 (2): 6274. Bibcode:2008SchpJ...3.6274A. doi:10.4249/scholarpedia.6274.
  4. ^ Lughofer, E.; Buchtala, O. (2013). "Reliable All-Pairs Evolving Fuzzy Classifiers". IEEE Transactions on Fuzzy Systems. 21 (4): 625–641. doi:10.1109/TFUZZ.2012.2226892. S2CID 29586197.


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