Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers-Reference-Cited by-同舟云学术

Mining multi-dimensional concept-drifting data streams using Bayesian network classifiers

Published:2016-03-01 Issue:2 Volume:20 Page:257-280
ISSN:1088-467X
Container-title:Intelligent Data Analysis
language:
Short-container-title:IDA

Author:

Borchani Hanen¹,Larrañaga Pedro¹,Gama João²,Bielza Concha¹

Affiliation:

1. Computational Intelligence Group, Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain

2. LIAAD-INESC Porto, Faculty of Economics, University of Porto, Porto, Portugal

Publisher

IOS Press

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Theoretical Computer Science

Reference41 articles.

1. Data Streams

2. Local causal and Markov blanket induction for causal discovery and feature selection for classification, Part I: Algorithms and empirical evaluation;Aliferis;Journal of Machine Learning Research,2010

3. Local causal and Markov blanket induction for causal discovery and feature selection for classification, Part II: Analysis and extensions;Aliferis;Journal of Machine Learning Research,2010

4. Multi-dimensional classification with Bayesian networks;Bielza;International Journal of Approximate Reasoning,2011

5. Bifet A., Holmes G., Pfahringer B., Kirkby R. and Gavaldà R., New ensemble methods for evolving data streams, in: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (2009), 139-148.

Cited by 12 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. Overview of Wind and Photovoltaic Data Stream Classification and Data Drift Issues;Energies;2024-09-01

2. Multi-dimensional classification: paradigm, algorithms and beyond;Vicinagearth;2024-06-25

3. Heuristic ensemble for unsupervised detection of multiple types of concept drift in data stream classification;Intelligent Decision Technologies;2022-01-10

4. Self-adjusting k nearest neighbors for continual learning from multi-label drifting data streams;Neurocomputing;2021-06

5. Multi-dimensional Bayesian network classifiers: A survey;Artificial Intelligence Review;2020-07-11