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Explaining the decisions of power quality disturbance classifiers using latent space features
Ram Machlev
, Michael Perl
, Avi Caciularu
, Juri Belikov
,
Kfir Yehuda Levy
,
Yoash Levron
Electrical and Computer Engineering
Technion - Israel Institute of Technology
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Keyphrases
Power Quality Disturbances
100%
Space Features
100%
Latent Space
100%
XAI Models
75%
Training Set
25%
Deep Learning
25%
Machine Learning Models
25%
Encoder-decoder
25%
Low Dimension
25%
Power System
25%
Feature Space
25%
Exceptional Performance
25%
Effect Modification
25%
Explainability
25%
Feature Ranking
25%
Power Quality Disturbance Classification
25%
Explainable Artificial Intelligence
25%
Easy-to-understand
25%
Computer Science
Feature Space
100%
Explainable Artificial Intelligence
100%
Deep Learning Technique
33%
Machine Learning Model
33%
Psychology
Explainable Artificial Intelligence
100%
Training Set
33%
Learning Model
33%