Transfer sample-based coupled task learning (TCTL)

Version 1.0.0.0 (564 ko) par Ke Yan
A multitask learning method with transfer samples
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Mise à jour 19 avr. 2016

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Simultaneously learning two models in two domains, with the help of transfer samples (reference / corresponding / calibration samples) in both domains.
Typical application: calibration transfer of two devices, or sensor drift correction.
Linear logistic regression and ridge regression under the framework of TCTL were implemented for classification and regression.
ref: K. Yan, and D. Zhang, “Calibration transfer and drift compensation of e-noses via coupled task learning," Sens. Actuators B: Chem., vol. 225, pp. 288-297, Mar., 2016.
Copyright 2015 YAN Ke, Tsinghua Univ. http://yanke23.com, xjed09@gmail.com

Citation pour cette source

Ke Yan (2026). Transfer sample-based coupled task learning (TCTL) (https://fr.mathworks.com/matlabcentral/fileexchange/54558-transfer-sample-based-coupled-task-learning-tctl), MATLAB Central File Exchange. Extrait(e) le .

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