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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 James
While 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 LNAI

Pagination

168-180

Location

SPAIN, Sant Cugat

Start date

2022-08-30

End date

2022-09-02

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783031134470

Language

English

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

Narukawa Y

Title 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 AG

Series

Lecture Notes in Artificial Intelligence