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Stability selection for LASSO with weights based on AUC
DC Field | Value | Language |
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dc.contributor.author | 서영주 | - |
dc.contributor.author | 정인경 | - |
dc.contributor.author | 한경화 | - |
dc.date.accessioned | 2023-04-20T08:34:08Z | - |
dc.date.available | 2023-04-20T08:34:08Z | - |
dc.date.issued | 2023-03 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/194122 | - |
dc.description.abstract | Stability selection is a variable selection algorithm based on resampling a dataset. Based on stability selection, we propose weighted stability selection to select variables by weighing them using the area under the receiver operating characteristic curve (AUC) from additional modelling. Through an extensive simulation study, we evaluated the performance of the proposed method in terms of the true positive rate (TPR), positive predictive value (PPV), and stability of variable selection. We also assessed the predictive ability of the method using a validation set. The proposed method performed similarly to stability selection in terms of the TPR, PPV, and stability. The AUC of the model fitted on the validation set with the selected variables of the proposed method was consistently higher in specific scenarios. Moreover, when applied to radiomics and speech signal datasets, the proposed method had a higher AUC with fewer variables selected. A major advantage of the proposed method is that it enables researchers to select variables intuitively using relatively simple parameter settings. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | Nature Publishing Group | - |
dc.relation.isPartOf | SCIENTIFIC REPORTS | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.subject.MESH | Algorithms* | - |
dc.subject.MESH | Area Under Curve | - |
dc.subject.MESH | Computer Simulation | - |
dc.subject.MESH | Predictive Value of Tests | - |
dc.subject.MESH | ROC Curve | - |
dc.subject.MESH | Retrospective Studies | - |
dc.title | Stability selection for LASSO with weights based on AUC | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Radiology (영상의학교실) | - |
dc.contributor.googleauthor | Yonghan Kwon | - |
dc.contributor.googleauthor | Kyunghwa Han | - |
dc.contributor.googleauthor | Young Joo Suh | - |
dc.contributor.googleauthor | Inkyung Jung | - |
dc.identifier.doi | 10.1038/s41598-023-32517-4 | - |
dc.contributor.localId | A01892 | - |
dc.contributor.localId | A03693 | - |
dc.contributor.localId | A04267 | - |
dc.relation.journalcode | J02646 | - |
dc.identifier.eissn | 2045-2322 | - |
dc.identifier.pmid | 36997611 | - |
dc.contributor.alternativeName | Suh, Young Joo | - |
dc.contributor.affiliatedAuthor | 서영주 | - |
dc.contributor.affiliatedAuthor | 정인경 | - |
dc.contributor.affiliatedAuthor | 한경화 | - |
dc.citation.volume | 13 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 5207 | - |
dc.identifier.bibliographicCitation | SCIENTIFIC REPORTS, Vol.13(1) : 5207, 2023-03 | - |
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