Enhancing Cluster Analysis With Explainable AI and Multidimensional Cluster Prototypes-Reference-Cited by-同舟云学术

Enhancing Cluster Analysis With Explainable AI and Multidimensional Cluster Prototypes

Published:2022 Issue: Volume:10 Page:101556-101574
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Bobek Szymon¹^ORCID,Kuk Michal²^ORCID,Szelazek Maciej²,Nalepa Grzegorz J.¹^ORCID

Affiliation:

1. Jagiellonian Human-Centered Artificial Intelligence Laboratory (JAHCAI), Jagiellonian University, Kraków, Poland

2. Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, Kraków, Poland

Funder

Narodowe Centrum Nauki

Priority Research Area (Digiworld) under the Strategic Programme Excellence Initiative at the Jagiellonian University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09900312.pdf?arnumber=9900312

Reference35 articles.

1. A Comparison of Information Criteria in Clustering Based on Mixture of Multivariate Normal Distributions

2. Explainable anomaly detection for Hot-rolling industrial process

3. Virtual Reality-Based Parallel Coordinates Plots Enhanced with Explainable AI and Data-Science Analytics for Decision-Making Processes

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