Publication Details

Increasing Classification Accuracy in LibSVM Using String Kernel Functions

HOMOLIAK, I. Increasing Classification Accuracy in LibSVM Using String Kernel Functions. Proceedings of the 18th Conference STUDENT EEICT 2012. Student EEICT, Volume 2. Brno: Faculty of Electrical Engineering and Communication BUT, 2012. p. 281-283. ISBN: 978-80-214-4461-4.

Czech title

Zvýšení úspěšnosti klasifikace v libSVM s použitím řetězcových fukcí

Type

conference paper

Language

English

Authors

Homoliak Ivan, Ing., Ph.D. (DITS)

Keywords

classification, libSVM, spam detection, string kernel functions

Abstract

This publication deal with classification of text data using string kernel functions and SVM. There are discussed various experiments with string kernel functions and SVM.

Annotation

This paper explores dependencies of text classification used with string kernel functions. There are described experiments with single string kernel function and also experiments with combinations of them with arithmetic operations of addition and multiplication. Gathered results are applied to detect spam messages of e-mail communication.

Published

2012

Pages

281–283

Proceedings

Proceedings of the 18th Conference STUDENT EEICT 2012

Series

Student EEICT, Volume 2

ISBN

978-80-214-4461-4

Publisher

Faculty of Electrical Engineering and Communication BUT

Place

Brno

BibTeX

@inproceedings{BUT98568,
  author="Ivan {Homoliak}",
  title="Increasing Classification Accuracy in LibSVM Using String Kernel Functions",
  booktitle="Proceedings of the 18th Conference STUDENT EEICT 2012",
  year="2012",
  series="Student EEICT, Volume 2",
  pages="281--283",
  publisher="Faculty of Electrical Engineering and Communication BUT",
  address="Brno",
  isbn="978-80-214-4461-4",
  url="https://www.fit.vut.cz/research/publication/10301/"
}