Wang, Xiaoke;
Zhu, Rui;
Xue, Jing-Hao;
(2025)
GKF-PUAL: A group kernel-free approach to positive-unlabeled learning with variable selection.
Information Sciences
, 690
, Article 121574. 10.1016/j.ins.2024.121574.
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Abstract
Variable selection is important for classification of data with many irrelevant predicting variables, but it has not yet been well studied in positive-unlabeled (PU) learning, where classifiers have to be trained without labelled-negative instances. In this paper, we propose a group kernel-free PU classifier with asymmetric loss (GKF-PUAL) to achieve quadratic PU classification with group-lasso regularisation embedded for variable selection. We also propose a five-block algorithm to solve the optimization problem of GKF-PUAL. Our experimental results reveal the superiority of GKF-PUAL in both PU classification and variable selection, improving the baseline PUAL by more than 10% in F1-score across four benchmark datasets and removing over 70% of irrelevant variables on six benchmark datasets. The code for GKF-PUAL is at https://github.com/tkks22123/GKF-PUAL.
| Type: | Article |
|---|---|
| Title: | GKF-PUAL: A group kernel-free approach to positive-unlabeled learning with variable selection |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ins.2024.121574 |
| Publisher version: | https://doi.org/10.1016/j.ins.2024.121574 |
| Language: | English |
| Additional information: | © 2024 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Positive-unlabeled learning, Group lasso, Kernel-free approach, Trifurcate data, Variable selection |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10205774 |
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