Aggregation of Subclassifications : Methods, Tools and Experiments

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2019
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2019 IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway, NJ: IEEE, 2019, pp. 3124-3131. ISBN 978-1-72812-485-8. Available under: doi: 10.1109/SSCI44817.2019.9002806
Zusammenfassung

Aggregation methods have been studied extensively from a mathematical, theoretical point of view. In this work, however, we focus on a more practical aspect: subclassifications. Given class predictions for several sub-objects of a single instance, we systematically investigate the performance of different aggregation methods. To this end, we simulate data for various data distributions. Thus we ensure that we know the ground truth for the evaluation, which would be impossible for real world data. Our source code is publicly available and can be extended to explore other aggregation methods and other data distributions.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
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classification, aggregation, sum, product, voting
Konferenz
2019 IEEE Symposium Series on Computational Intelligence (SSCI), 6. Dez. 2019 - 9. Dez. 2019, Xiamen, China
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Zitieren
ISO 690DOELL, Christoph, Christian BORGELT, 2019. Aggregation of Subclassifications : Methods, Tools and Experiments. 2019 IEEE Symposium Series on Computational Intelligence (SSCI). Xiamen, China, 6. Dez. 2019 - 9. Dez. 2019. In: 2019 IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway, NJ: IEEE, 2019, pp. 3124-3131. ISBN 978-1-72812-485-8. Available under: doi: 10.1109/SSCI44817.2019.9002806
BibTex
@inproceedings{Doell2019Aggre-53223,
  year={2019},
  doi={10.1109/SSCI44817.2019.9002806},
  title={Aggregation of Subclassifications : Methods, Tools and Experiments},
  isbn={978-1-72812-485-8},
  publisher={IEEE},
  address={Piscataway, NJ},
  booktitle={2019 IEEE Symposium Series on Computational Intelligence (SSCI)},
  pages={3124--3131},
  author={Doell, Christoph and Borgelt, Christian}
}
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