Tropical Support Vector Machines: Evaluations and Extension to Function Spaces. (arXiv:2101.11531v2 [cs.LG] UPDATED)

Support Vector Machines (SVMs) are one of the most popular supervised
learning models to classify using a hyperplane in an Euclidean space. Similar
to SVMs, tropical SVMs classify data points using a tropical hyperplane under
the tropical metric with the max-plus algebra. In this paper, first we show
generalization error bounds of tropical SVMs over the tropical projective
torus. While the generalization error bounds attained via Vapnik-Chervonenkis
(VC) dimensions in a distribution-free manner still depend on the dimension, we
also …

arxiv extension function machines support vector