Chain Graph Explanation of Neural Network Based on Feature-Level Class Confusion
Despite increasing interest in developing interpretable machine learning methods, most recent studies have provided explanations only for single instances, require additional datasets, and are sensitive to hyperparameters. This paper proposes a confusion graph that reveals model weaknesses by constr...
Main Authors: | Hyekyoung Hwang, Eunbyung Park, Jitae Shin |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-01-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/3/1523 |
Similar Items
-
Neural Image Compression and Explanation
by: Xiang Li, et al.
Published: (2020-01-01) -
Metrics and Evaluations of Time Series Explanations: An Application in Affect Computing
by: Nazanin Fouladgar, et al.
Published: (2022-01-01) -
User‐guided global explanations for deep image recognition: A user study
by: Mandana Hamidi‐Haines, et al.
Published: (2021-12-01) -
Explanations for Neural Networks by Neural Networks
by: Sascha Marton, et al.
Published: (2022-01-01) -
Explaining Intrusion Detection-Based Convolutional Neural Networks Using Shapley Additive Explanations (SHAP)
by: Remah Younisse, et al.
Published: (2022-10-01)