Transfer sample-based coupled task learning (TCTL)
A multitask learning method with transfer samples
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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
Cite As
Ke Yan (2026). Transfer sample-based coupled task learning (TCTL) (https://www.mathworks.com/matlabcentral/fileexchange/54558-transfer-sample-based-coupled-task-learning-tctl), MATLAB Central File Exchange. Retrieved .
General Information
- Version 1.0.0.0 (564 KB)
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0.0 | url updated |
