A short note about the application of polynomial kernels with fractional degree in support vector learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1398, Issue , 1998, Pages 143-148

  Rossius, Rolf ^a   Zenker, Gérard ^a   Ittner, Andreas ^a   Dilger, Werner ^a  

^a CHEMNITZ UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION TREES; MACHINE LEARNING; POLYNOMIALS; QUADRATIC PROGRAMMING;

DECISION TREE METHOD; FEATURE SPACE; INFINITE DIMENSIONS; MACHINE LEARNING APPROACHES; POLYNOMIAL KERNELS; SUPPORT VECTOR LEARNING;

SUPPORT VECTOR MACHINES;

EID: 84896401783     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/bfb0026684     Document Type: Conference Paper

References (4)

1. [CV95] C. Cortes and V. N. Vapnik. Support-vector networks. Machine Learning, 20:273-297, 1995.
2. [Fri93] B. Fritzke. Growing cell structures - a self-organizing network for unsupervised and supervised learning. Technical Report 93-026, International Computer Science Institute, Berkeley, California, 1993.
3. [IRZ98] A. Ittner, R. Rossius, and G. Zenker. Support Vector Learning. Technical Report CSR-98, Chemnitz University of Technology, Chemnitz, Germany, 1998.
4. [Vap95] V. N. Vapnik. The Nature of Statistical Learning Theory. Springer-Verlag,1995.