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Chance constrained conic-segmentation support vector machine with uncertain data. (arXiv:2107.13319v2 [cs.LG] UPDATED)
cs.LG updates on arXiv.org arxiv.org
Support vector machines (SVM) is one of the well known supervised classes of
learning algorithms. Furthermore, the conic-segmentation SVM (CS-SVM) is a
natural multiclass analogue of the standard binary SVM, as CS-SVM models are
dealing with the situation where the exact values of the data points are known.
This paper studies CS-SVM when the data points are uncertain or mislabelled.
With some properties known for the distributions, a chance-constrained CS-SVM
approach is used to ensure the small probability of misclassification …