Feb 27, 2020 · A new AUC-based least squares support vector machine called AUC-LS-SVMs is proposed for directly and effectively classifying imbalanced prostate cancer data.
Abstract Quite often, the available pre-biopsy data for early prostate cancer detection are imbalanced. When the least squares support vector machines ...
Least squares support vector machines with fast leave-one-out AUC optimization on imbalanced prostate cancer data. G. Wang, J.Y.C. Teoh, J. Lu and K-S Choi
Feb 27, 2020 · The distinctive advantage of the proposed classifier AUC-LS-SVMs exists in that it can achieve the minimal leave-one-out error by quickly ...
The distinctive advantage of the proposed classifier AUC-LS-SVMs exists in that it can achieve the minimal leave-one-out error by quickly optimizing the ...
Article: Least squares support vector machines with fast leave-one-out AUC optimization on imbalanced prostate cancer data.
Least squares support vector machines with fast leave-one-out AUC optimization on imbalanced prostate cancer data · Wang, G; Teoh, JYC ...
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Least squares support vector machines with fast leave-one-out AUC optimization on imbalanced prostate cancer data. Article. Full-text available. Aug 2020.
Support Vector Machine is used for early differential diagnosis of PCa. Model (SVM-PCa-EDD) performance shows 90% accurate, 80% sensitive and 80% specificity.
Jan 10, 2022 · WangG. et al. Least squares support vector machines with fast leave-one-out AUC optimization on imbalanced prostate cancer data ...