Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Single Class Universum-SVM   This paper extends the idea of Universum learning [1, 2] to single-class
learning problems. We propose Single Class Universum-SVM setting that
incorporates a priori knowledge (in the form of additional data samples) into
the single class estimation problem. These additional data samples or Universum
belong to the same application domain as (positive) data samples from a single
class (of interest), but they follow a different distribution. Proposed
methodology for single class U-SVM is based on the known connection between
binary classification and single class learning formulations [3]. Several
empirical comparisons are presented to illustrate the utility of the proposed
approach.

37
The categories of this paper are: supr-con
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
27
The categories of this paper are: comp-gas
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat