Genetic Programming for Document Classification: A Transductive Transfer Learning System

Created by W.Langdon from gp-bibliography.bib Revision:1.7975

@Article{Fu:2024:CYB,

• author = "Wenlong Fu and Bing Xue and Xiaoying Gao and Mengjie Zhang",
• journal = "IEEE Transactions on Cybernetics",
• title = "Genetic Programming for Document Classification: A Transductive Transfer Learning System",
• year = "2024",
• volume = "54",
• number = "2",
• pages = "1119--1132",
• month = feb,
• keywords = "genetic algorithms, genetic programming, Transfer learning, Training, Training data, Task analysis, Feature extraction, Support vector machines, SVM, Data models, Document classification, pseudolabel, transductive transfer learning",
• ISSN = "2168-2275",
• DOI = "doi:10.1109/TCYB.2023.3338266",
• size = "14 pages",
• abstract = "Document classification is a challenging task to the data being high-dimensional and sparse. Many transfer learning methods have been investigated for improving the classification performance by effectively transferring knowledge from a source domain to a target domain, which is similar to but different from the source domain. However, most of the existing methods cannot handle the case that the training data of the target domain does not have labels. In this study, we propose a transductive transfer learning system, using solutions evolved by genetic programming (GP) on a source domain to automatically pseudolabel the training data in the target domain in order to train classifiers. Different from many other transfer learning techniques, the proposed system pseudolabels target-domain training data to retrains classifiers using all target-domain features. The proposed method is examined on nine transfer learning tasks, and the results show that the proposed transductive GP system has better prediction accuracy on the test data in the target domain than existing transfer learning approaches including subspace alignment-domain adaptation methods, feature-level-domain adaptation methods, and one latest pseudolabeling strategy-based method.",
• notes = "Also known as \cite{10367876}",

}

Genetic Programming entries for Wenlong Fu Bing Xue Xiaoying (Sharon) Gao Mengjie Zhang

Citations