Classification and feature selection methods based on fitting logistic regression to PU data-Reference-Cited by-同舟云学术

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Classification and feature selection methods based on fitting logistic regression to PU data

Published:2023-09 Issue: Volume:72 Page:102095
ISSN:1877-7503
Container-title:Journal of Computational Science
language:en
Short-container-title:Journal of Computational Science

Author:

Furmańczyk Konrad^ORCID,Paczutkowski Kacper^ORCID,Dudziński Marcin^ORCID,Dziewa-Dawidczyk Diana^ORCID

Publisher

Elsevier BV

Subject

Modeling and Simulation,General Computer Science,Theoretical Computer Science

Reference32 articles.

1. Web Data Mining;Liu,2007

2. Semi-supervised learning;Chapelle;IEEE Trans. Neural Netw.,2009

3. Learning from positive and unlabeled data: a survey;Bekker,2020

4. One-class classifcation: Taxonomy of study and review of techniques;Khan;Knowl. Eng. Rev.,2014

5. Learning with positive and unlabeled examples using weighted logistic regression;Lee,2003

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The computational planet;Journal of Computational Science;2023-09

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