The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 88-338
Full Name: Iuliana Paraschiv-Munteanu
Position: Senior Lecturer
Age: ON
Sex: Female
Address: University of Bucharest, Faculty of Mathematics and Computer Science, 14 Academiei St., Bucharest, 010014
Country: ROMANIA
Tel: 040721-205355
Tel prefix:
Fax:
E-mail address: pmiulia@fmi.unibuc.ro
Other E-mails: iuliana.munteanu@gmail.com, lstate@clicknet.ro
Title of the Paper: SVM-based Supervised and Unsupervised Classification Schemes
Authors as they appear in the Paper: Luminita State, Iuliana Paraschiv-Munteanu
Email addresses of all the authors: lstate@clicknet.ro, pmiulia@fmi.unibuc.ro
Number of paper pages: 12
Abstract: The aim of the research reported is to propose a training algorithm for support vector machine based on kernel functions and to test its performance in case of non-linearly separable data. The training is based on the Sequential Minimal Optimization introduced by J.C. Platt in 1999. Several classifications schemes resulted by combining the SVM and the 2-means methods are proposed in the fifth section of the paper. A series of conclusions derived experimentally concerning the comparative analysis of the performances proved by the proposed methods are summarized in the final part of the paper. The tests were performed on samples randomly generated from Gaussian two-dimensional distributions, and on data available in Wisconsin Diagnostic Breast Cancer Database.
Keywords: Support Vector Machine, Pattern recognition, Statistical learning theory, Kernel functions, Principal Components Analysis, k-means Algorithm
EXTENSION of the file: .pdf
Special (Invited) Session: The Analysis of a Faster Algorithm for Support Vector Machine-based Classification
Organizer of the Session: 646-407
How Did you learn about congress: Prof.dr. Tudor Balanescu, tudor_balanescu@yahoo.com
IP ADDRESS: 188.27.119.80
