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Cluster-Based Active Learning

version 1.0.1 (167 KB) by Lawrence Bull
Package and demo details at [https://github.com/labull/cluster_based_active_learning]

18 Downloads

Updated 08 Nov 2018

View License on GitHub

- This software implements cluster-based active learning in MATLAB, via Dasgupta's and Hsu's (DH) Algorithm.

- The original paper for the DH algorithm can be found at [http://icml2008.cs.helsinki.fi/papers/324.pdf]; cite to credit the authors.

- This code was written for engineering applications. Algorithm details can be found at [https://www.sciencedirect.com/science/article/pii/S0022460X18305479?via%3Dihub]; cite if you use this software.

If you find any bugs/errors in the code, get in contact via the GitHub issues tab.
Package and demo details at [https://github.com/labull/cluster_based_active_learning]

Cite As

@article{BULL2018373, title = "Active learning for semi-supervised structural health monitoring", journal = "Journal of Sound and Vibration", volume = "437", pages = "373 - 388", year = "2018", issn = "0022-460X", doi = "https://doi.org/10.1016/j.jsv.2018.08.040", url = "http://www.sciencedirect.com/science/article/pii/S0022460X18305479", author = "L. Bull and K. Worden and G. Manson and N. Dervilis", keywords = "Structural health monitoring, Vibration monitoring, Active learning, Semi-supervised learning, Classification, Pattern recognition", }

L. Bull, K. Worden, G. Manson, N. Dervilis, Active learning for semi-supervised structural health monitoring, Journal of Sound and Vibration, Volume 437, 2018, Pages 373-388, ISSN 0022-460X.

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Updates

1.0.1

updated description and screenshot

MATLAB Release Compatibility
Created with R2018b
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: Cluster-Based Active Learning

Inspired: Cluster-Based Active Learning

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