QuadCDD: A Quadruple-based Approach for Understanding Concept Drift in Data Streams-Reference-Cited by-同舟云学术

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QuadCDD: A Quadruple-based Approach for Understanding Concept Drift in Data Streams

Published:2024-03 Issue: Volume:238 Page:122114
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Wang Pingfan^ORCID,Yu Hang,Jin Nanlin^ORCID,Davies Duncan,Woo Wai Lok^ORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference55 articles.

1. Hierarchical change-detection tests;Alippi;IEEE Transactions on Neural Networks and Learning Systems,2017

2. Early drift detection method;Baena-Garcıa,2006

3. Detecting concept drift with neural network model uncertainty;Baier,2021

4. Learning from time-changing data with adaptive windowing;Bifet,2007

5. Is out-of-distribution detection learnable?;Fang,2022

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. JEM: An AI-based engine workflow to predict simulation’s execution time on HPC cluster;2024 International Conference on Control, Automation and Diagnosis (ICCAD);2024-05-15

2. A comprehensive analysis of concept drift locality in data streams;Knowledge-Based Systems;2024-04

3. Deep Capsnets Leaning with a New Dynamic Routing Algorithm for Drift Detection;2024

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