Probabilistic Active Learning: Uncertainty Sampling

Versione 1.0.2 (281 Byte) da Lawrence Bull
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Aggiornato 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).

Cita come

@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.

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Creato con R2019b
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Versione Pubblicato Note della release
1.0.2

citation updates
1.0.1

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1.0.0

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