Probabilistic Active Learning: Uncertainty Sampling

Version 1.0.2 (281 Bytes) by Lawrence Bull
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Updated 18 Mar 2021
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- This code implements active learning through uncertainty sampling within a Gaussian Mixture Model (GMM), considering applications to streaming data.

- The code was written for engineering applications (structural health monitoring), implementation details can be found at [https://www.sciencedirect.com/science/article/pii/S0888327019305096], a paper published in Mechanical Systems and Signal Processing (MSSP).

Cite As

@article{BULL2019106294, title = "Probabilistic active learning: An online framework for structural health monitoring", journal = "Mechanical Systems and Signal Processing", volume = "134", pages = "106294", year = "2019", author = "L.A. Bull and T.J. Rogers and C. Wickramarachchi and E.J. Cross and K. Worden and N. Dervilis"}

Bull, L.A., Rogers, T.J., Wickramarachchi, C., Cross, E.J., Worden, K. and Dervilis, N., 2019. Probabilistic active learning: An online framework for structural health monitoring. Mechanical Systems and Signal Processing, 134, p.106294.

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
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Version Published Release Notes
1.0.2

citation updates
1.0.1

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1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.