Classification with incomplete data and ensemble learners for the prediction of cervical cancer risk
| dc.authorscopusid | 6505872114 | |
| dc.contributor.author | Yildirim,P. | |
| dc.date.accessioned | 2024-05-25T12:32:26Z | |
| dc.date.available | 2024-05-25T12:32:26Z | |
| dc.date.issued | 2018 | |
| dc.department | Okan University | en_US |
| dc.department-temp | Yildirim P., Department of Computer Engineering, Faculty of Engineering, Okan University, Istanbul, Turkey | en_US |
| dc.description.abstract | Incomplete data is an important problem in analyzing medical data sets. In this study, a comparative analysis of ensemble learning algorithms was carried out for the prediction of cervical cancer risk with incomplete data. Cervical cancer is one of the most common cancers for women world-wide, and many researchers focused on this disease. The dataset was collected from UCI Machine Learning Repository. Mean imputation was used to deal with missing values and some ensemble and standalone classifiers were used to analyze the dataset for the evaluation of the performance. This study supported that imputation approaches and ensemble learning can improve the performance of learning algorithms. © 2018 Association for Computing Machinery. | en_US |
| dc.identifier.citationcount | 1 | |
| dc.identifier.doi | 10.1145/3233740.3233741 | |
| dc.identifier.endpage | 5 | en_US |
| dc.identifier.isbn | 978-145036461-4 | |
| dc.identifier.scopus | 2-s2.0-85055879140 | |
| dc.identifier.startpage | 1 | en_US |
| dc.identifier.uri | https://doi.org/10.1145/3233740.3233741 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14517/2387 | |
| dc.language.iso | en | |
| dc.publisher | Association for Computing Machinery | en_US |
| dc.relation.ispartof | ACM International Conference Proceeding Series -- 2018 International Conference on Intelligent Science and Technology, ICIST 2018 -- 30 June 2018 through 2 July 2018 -- London -- 140165 | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.scopus.citedbyCount | 1 | |
| dc.subject | AdaBoostM1 | en_US |
| dc.subject | RandomSubSpace | en_US |
| dc.subject | Stacking | en_US |
| dc.subject | Vote. | en_US |
| dc.title | Classification with incomplete data and ensemble learners for the prediction of cervical cancer risk | en_US |
| dc.type | Conference Object | en_US |