Leverage estimation for multi-output neural networks

Tomasz Grel , Stanisław Jankowski


The article deals with the problem of computing the leverages for multi-output neural networks. The leverages can be subsequently used for determining which learning examples have the strongest influence on the model. Therefore computing them may provide researchers with important insights about the constructed model. More specifically they can be used to detect overfitting. A step by step algorithm for computing the Jacobian matrix and the leverages is presented, along with an example application to a synthetic problem.
Author Tomasz Grel
Tomasz Grel,,
, Stanisław Jankowski (FEIT / PE)
Stanisław Jankowski,,
- The Institute of Electronic Systems
Pages 100315D-1- 100315D-6
Publication size in sheets0.5
Book Romaniuk Ryszard (eds.): Proc. SPIE. 10031, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2016, vol. 10031, 2016, P.O. Box 10, Bellingham, Washington 98227-0010 USA , SPIE , ISBN 9781510604858, [781510604865 (electronic) ], 1170 p., DOI:10.1117/12.2257157
Keywords in EnglishDimensionality reduction, influence statistics, leverages, hat matrix, artificial neural networks, Nonlinear PCA, overfitting
URL http://dx.doi.org.spiedl.eczyt.bg.pw.edu.pl/10.1117/12.2249699
Languageen angielski
100315D_Grel.pdf 296.28 KB
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 10-01-2020, BookChapterMatConfByConferenceseries
Ministerial score (2013-2016) = 15.0, 10-01-2020, BookChapterMatConfByConferenceseries
Publication indicators WoS Citations = 0
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