Receiver operating characteristic curves and confidence bands for support vector machines.

TitleReceiver operating characteristic curves and confidence bands for support vector machines.
Publication TypeJournal Article
Year of Publication2021
AuthorsLuckett, Daniel J., Eric B. Laber, Samer S. El-Kamary, Cheng Fan, Ravi Jhaveri, Charles M. Perou, Fatma M. Shebl, and Michael R. Kosorok
JournalBiometrics
Volume77
Issue4
Pagination1422-1430
Date Published2021 12
ISSN1541-0420
KeywordsBreast Neoplasms, Computer Simulation, Female, Humans, Probability, ROC Curve, Support Vector Machine
Abstract

Many problems that appear in biomedical decision-making, such as diagnosing disease and predicting response to treatment, can be expressed as binary classification problems. The support vector machine (SVM) is a popular classification technique that is robust to model misspecification and effectively handles high-dimensional data. The relative costs of false positives and false negatives can vary across application domains. The receiving operating characteristic (ROC) curve provides a visual representation of the trade-off between these two types of errors. Because the SVM does not produce a predicted probability, an ROC curve cannot be constructed in the traditional way of thresholding a predicted probability. However, a sequence of weighted SVMs can be used to construct an ROC curve. Although ROC curves constructed using weighted SVMs have great potential for allowing ROC curves analyses that cannot be done by thresholding predicted probabilities, their theoretical properties have heretofore been underdeveloped. We propose a method for constructing confidence bands for the SVM ROC curve and provide the theoretical justification for the SVM ROC curve by showing that the risk function of the estimated decision rule is uniformly consistent across the weight parameter. We demonstrate the proposed confidence band method using simulation studies. We present a predictive model for treatment response in breast cancer as an illustrative example.

DOI10.1111/biom.13365
Alternate JournalBiometrics
Original PublicationReceiver operating characteristic curves and confidence bands for support vector machines.
PubMed ID32865820
PubMed Central IDPMC7914290
Grant ListUL1 TR001111 / TR / NCATS NIH HHS / United States
U01 HD039164 / HD / NICHD NIH HHS / United States
UL1 TR002489 / TR / NCATS NIH HHS / United States
P50 CA058223 / CA / NCI NIH HHS / United States
U01 AI058372 / AI / NIAID NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
T32 CA201159 / CA / NCI NIH HHS / United States
R01 DE024984 / DE / NIDCR NIH HHS / United States
K23 DK059311 / DK / NIDDK NIH HHS / United States