A Discriminative Dictionary Learning-AdaBoost-SVM Classification Method on Imbalanced Datasets
| dc.contributor.author | Barstugan, Mucahid | |
| dc.contributor.author | Ceylan, Rahime | |
| dc.date.accessioned | 2020-03-26T19:33:26Z | |
| dc.date.available | 2020-03-26T19:33:26Z | |
| dc.date.issued | 2017 | |
| dc.department | Selçuk Üniversitesi | en_US |
| dc.description | 2017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEY | en_US |
| dc.description.abstract | Sparse representation is a signal processing method which is mostly used in signal compression, noise reduction, and signal and image restoration fields. In this study, sparse representation was used in a different way from the traditional methods. In the proposed method, a hybrid structure was created by combining dictionary learning and ensemble classifier AdaBoost algorithms. The main idea of this method is to obtain the sparse coefficients from an over-complete dictionary and to use the coefficients in the weight update formula of AdaBoost. Support Vector Machines (SVM) classifier was used as weak classifiers of AdaBoost, and AdaBoost-SVM classifier structure was created. Multiplying the sparse coefficients with weight of weak learners process in weight update formula has given satisfying results on imbalanced datasets during the experiments. | en_US |
| dc.description.sponsorship | IEEE Turkey Sect, Anatolian Sci | en_US |
| dc.description.sponsorship | Coordinatorship of Selcuk University's Scientific Research ProjectsSelcuk University | en_US |
| dc.description.sponsorship | This work was supported by the Coordinatorship of Selcuk University's Scientific Research Projects. | en_US |
| dc.identifier.isbn | 978-1-5386-1880-6 | |
| dc.identifier.scopusquality | N/A | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12395/34718 | |
| dc.identifier.wos | WOS:000426868700177 | en_US |
| dc.identifier.wosquality | N/A | en_US |
| dc.indekslendigikaynak | Web of Science | en_US |
| dc.indekslendigikaynak | Scopus | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.ispartof | 2017 INTERNATIONAL ARTIFICIAL INTELLIGENCE AND DATA PROCESSING SYMPOSIUM (IDAP) | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.selcuk | 20240510_oaig | en_US |
| dc.subject | dictionary learning | en_US |
| dc.subject | ensemble classifiers | en_US |
| dc.subject | sparse representation | en_US |
| dc.subject | weak classifiers | en_US |
| dc.subject | weight update | en_US |
| dc.title | A Discriminative Dictionary Learning-AdaBoost-SVM Classification Method on Imbalanced Datasets | en_US |
| dc.type | Conference Object | en_US |
