Publikation:

Supervised Learning in Parallel Universes using Neighborgrams

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2011

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http://nbn-resolving.de/urn:nbn:de:bsz:352-193242
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https://doi.org/10.1007/978-3-642-24800-9_36
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GAMA, João, ed., Elizabeth BRADLEY, ed., Jaakko HOLLMÉN, ed.. Advances in Intelligent Data Analysis X. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 388-400. Lecture Notes in Computer Science. 7014. ISBN 978-3-642-24799-6. Available under: doi: 10.1007/978-3-642-24800-9_36

Zusammenfassung

We present a supervised method for Learning in Parallel Universes, i.e. problems given in multiple descriptor spaces. The goal is the construction of local models in individual universes and their fusion to a superior global model that comprises all the available information from the given universes. We employ a predictive clustering approach using Neighborgrams, a one-dimensional data structure for the neighborhood of a single object in a universe. We also present an intuitive visualization, which allows for interactive model construction and visual comparison of cluster neighborhoods across universes.

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ISO 690WISWEDEL, Bernd, Michael R. BERTHOLD, 2011. Supervised Learning in Parallel Universes using Neighborgrams. In: GAMA, João, ed., Elizabeth BRADLEY, ed., Jaakko HOLLMÉN, ed.. Advances in Intelligent Data Analysis X. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011, pp. 388-400. Lecture Notes in Computer Science. 7014. ISBN 978-3-642-24799-6. Available under: doi: 10.1007/978-3-642-24800-9_36
BibTex
@inproceedings{Wiswedel2011Super-19324,
  year={2011},
  doi={10.1007/978-3-642-24800-9_36},
  title={Supervised Learning in Parallel Universes using Neighborgrams},
  number={7014},
  isbn={978-3-642-24799-6},
  publisher={Springer Berlin Heidelberg},
  address={Berlin, Heidelberg},
  series={Lecture Notes in Computer Science},
  booktitle={Advances in Intelligent Data Analysis X},
  pages={388--400},
  editor={Gama, João and Bradley, Elizabeth and Hollmén, Jaakko},
  author={Wiswedel, Bernd and Berthold, Michael R.}
}
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