Streaming Data Classification Based on Hierarchical Concept Drift and Online Ensemble
Author:
Affiliation:
1. Faculty of Economics and Management, Shangluo University, Shangluo, China
2. Engineering Research Center of Qinling Health Welfare Big Data, Universities of Shaanxi Province, Shangluo, China
Funder
Natural Science Basic Research Program of Shaanxi
Science and Technology Planning Project of Shangluo City
Natural Science Research Project of Shangluo University
Shangluo Universities Key Disciplines Project
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/ielx7/6287639/10005208/10295435.pdf?arnumber=10295435
Reference31 articles.
1. Reacting to Different Types of Concept Drift: The Accuracy Updated Ensemble Algorithm
2. Adaptive Chunk-Based Dynamic Weighted Majority for Imbalanced Data Streams With Concept Drift
3. Selective ensemble-based online adaptive deep neural networks for streaming data with concept drift
4. Incremental Learning of Concept Drift in Nonstationary Environments
5. Online ensemble adaptive algorithm for concept drift of streaming data;cui;Journal of Nanjing Univ( Natural Sciences),2023
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