Multi-category classifiers and sample width
Anthony, M.
& Ratsaby, J.
(2016).
Multi-category classifiers and sample width.
Journal of Computer and System Sciences,
82(8), 1223-1231.
https://doi.org/10.1016/j.jcss.2016.04.003
& Ratsaby, J.
(2016).
Multi-category classifiers and sample width.
Journal of Computer and System Sciences,
82(8), 1223-1231.
https://doi.org/10.1016/j.jcss.2016.04.003
In a recent paper, the authors introduced the notion of sample width for binary classifier defined on the set of real numbers. It was shown that the performance of such classifier could be quantified in terms of this sample width. This paper considers how to adapt the idea of sample width so that it can be applied in cases where the classifier are multi-category and are defined on some arbitrary metric space.