GAMI-Net: An explainable neural network based on generalized additive models with structured interactions
•A novel explainable neural network is proposed for modeling main effects and structured interactions.•The GAMI-Net is a disentangled feedforward network with multiple additive subnetworks.•GAMI-Net takes into account three interpretability constraints: sparsity, heredity, marginal clarity.•An adapt...
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Published in | Pattern recognition Vol. 120; p. 108192 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.12.2021
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Subjects | |
Online Access | Get full text |
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