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Representation and Interpretability of IE Integral Neural Networks
conference contribution
posted on 2023-02-21, 03:53 authored by A Honda, Y Kamata, Simon JamesSimon JamesWhile there has been a lot of research attention given to neural networks and other black-box machine learning methods, recent works on aggregation functions and fuzzy sets have highlighted the appeal of incorporating fuzzy integrals into network implementations in order to achieve interpretability. We present an application of the recently proposed inclusion-exclusion integral neural network to the Boston House-Price dataset to illustrate its potential and examine the settings leading to better performance.
History
Volume
13408 LNAIPagination
168-180Location
SPAIN, Sant CugatPublisher DOI
Start date
2022-08-30End date
2022-09-02ISSN
0302-9743eISSN
1611-3349ISBN-13
9783031134470Language
EnglishPublication classification
E1 Full written paper - refereedEditor/Contributor(s)
Narukawa YTitle of proceedings
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Event
19th International Conference on Modeling Decisions for Artificial Intelligence (MDAI)Publisher
SPRINGER INTERNATIONAL PUBLISHING AGSeries
Lecture Notes in Artificial IntelligenceUsage metrics
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