Data Mining Using Support Vector Machines

Chamasemani, Fereshteh Falah (2011) Data Mining Using Support Vector Machines. Masters thesis, Multimedia University.

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Abstract

The objectives of this work are; first to propose BbSVM and BmSVM as new boosting algorithms for enhancing the accuracy and performance of common SVM. Second,to show the robustness of various kind of kernels for BbSVM and BmSVM classifiers,and a comparison of different constructing methods for Multi-class SVM,like One-Against-All,One-Against-One Binary Tree and Directed Acyclic Graph.

Item Type: Thesis (Masters)
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Users 1102 not found.
Date Deposited: 03 Dec 2012 01:31
Last Modified: 03 Dec 2012 01:31
URI: http://shdl.mmu.edu.my/id/eprint/3653

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