Result 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.
Type
conference paper
Language
English
Authors
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.
Keywords
classification, libSVM, spam detection, string kernel functions
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
Conference
Student EEICT 2012
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/"
}
Files
Projects
Security-Oriented Research in Information Technology, MŠMT, Institucionální prostředky SR ČR (např. VZ, VC), MSM0021630528, start: 2007-01-01, end: 2013-12-31, running
Research groups
IT Security Research Group (RG Security@FIT)
Departments