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Stability selection for LASSO with weights based on AUC

 Yonghan Kwon  ;  Kyunghwa Han  ;  Young Joo Suh  ;  Inkyung Jung 
 SCIENTIFIC REPORTS, Vol.13(1) : 5207, 2023-03 
Journal Title
Issue Date
Algorithms* ; Area Under Curve ; Computer Simulation ; Predictive Value of Tests ; ROC Curve ; Retrospective Studies
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.
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Appears in Collections:
1. College of Medicine (의과대학) > Research Institute (부설연구소) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Suh, Young Joo(서영주) ORCID logo https://orcid.org/0000-0002-2078-5832
Jung, Inkyung(정인경) ORCID logo https://orcid.org/0000-0003-3780-3213
Han, Kyung Hwa(한경화)
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