Title
Separability of set-valued data sets and existence of support hyperplanes in the support function machine.
Abstract
The support function machine (SFM) has been shown to be effective in separating set-valued data sets. However, in SFM, the separability of set-valued data and the existence of support hyperplanes, which can provide useful guidance for improving algorithms for use in applications, have not been discussed in theory. Therefore, in this paper, we firstly discuss the problem of whether the linearly separable set-valued data in Rd are still linearly separable after being mapped into the infinite-dimensional Banach space C(S) by support functions. Secondly, we discuss the problem of whether the linearly inseparable set-valued data in Rd are linearly separable after being mapped into C(S). If not, in which situations are they linearly separable? Thirdly, we discuss the existence of support hyperplanes in SFM. Finally, two experiments with set-valued data sets are provided to verify the reasoning in the above discussions and the correctness of their conclusions.
Year
DOI
Venue
2018
10.1016/j.ins.2017.11.057
Information Sciences
Keywords
Field
DocType
Support vector machine,Set-valued data,Separability,Support hyperplane,Support function
Linear separability,Discrete mathematics,Support function,Data set,Correctness,Banach space,Hyperplane,Mathematics
Journal
Volume
ISSN
Citations 
430
0020-0255
0
PageRank 
References 
Authors
0.34
21
4
Name
Order
Citations
PageRank
Jiqiang Chen1284.60
Xiaoping Xue218617.00
Litao Ma3203.00
Ming-Hu Ha413722.51