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Digital
Library of the European Council for Modelling and Simulation |
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Title: |
Estimating Relationships
In Multi-Dimensional Data Sets By Means Of Asymmetric Fuzzy Regression |
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Authors: |
Raphael
A. Krauthann, Tobias Kruse, Hinnerk
Jannis Mueller, Michael Stumpf,
Peter Rausch |
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Published in:
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2020). ECMS 2020 Proceedings
Edited by: Mike Steglich, Christian Muller, Gaby
Neumann, Mathias Walther, European Council for Modeling and Simulation. DOI: http://doi.org/10.7148/2020 ISSN:
2522-2422 (ONLINE) ISSN:
2522-2414 (PRINT) ISSN:
2522-2430 (CD-ROM) ISBN: 978-3-937436-68-5 Communications of the ECMS , Volume 34, Issue 1, June 2020, United Kingdom |
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Citation
format: |
Raphael A. Krauthann, Tobias Kruse, Hinnerk Jannis Mueller, Michael Stumpf, Peter Rausch (2020). Estimating Relationships In Multi-Dimensional Data Sets By Means Of Asymmetric Fuzzy Regression, ECMS 2020 Proceedings Edited By: Mike Steglich, Christian Mueller, Gaby Neumann, Mathias Walther European Council for Modeling and Simulation. doi: 10.7148/2020-0197 |
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DOI: |
https://doi.org/10.7148/2020-0197 |
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Abstract: |
In spite of
all progress of AI and Machine Learning, making predictions based on
real-world data is still a challenging task. For this purpose, Tanaka's
approach of symmetric fuzzy linear regression is explained, and open issues
are outlined. These issues occur if the instances of data sets are not
symmetrically distributed. For this purpose, new solutions based on
enhancements of Tanaka's approach are discussed. A real-world scenario for predicting
house prices is used to illustrate the ideas. It is shown that the new
asymmetric approach works at least as well as the symmetric version but is superior
in certain situations. |
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