Commenced in January 2007
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Paper Count: 1

Multi-Classification Related Publications

1 Genetic Folding: Analyzing the Mercer-s Kernels Effect in Support Vector Machine using Genetic Folding

Authors: Maysam F. Abbod, Mohd A. Mezher

Abstract:

Genetic Folding (GF) a new class of EA named as is introduced for the first time. It is based on chromosomes composed of floating genes structurally organized in a parent form and separated by dots. Although, the genotype/phenotype system of GF generates a kernel expression, which is the objective function of superior classifier. In this work the question of the satisfying mapping-s rules in evolving populations is addressed by analyzing populations undergoing either Mercer-s or none Mercer-s rule. The results presented here show that populations undergoing Mercer-s rules improve practically models selection of Support Vector Machine (SVM). The experiment is trained multi-classification problem and tested on nonlinear Ionosphere dataset. The target of this paper is to answer the question of evolving Mercer-s rule in SVM addressed using either genetic folding satisfied kernel-s rules or not applied to complicated domains and problems.

Keywords: Genetic Programming, Evolutionary Algorithms, Genetic Algorithm, support vector machine, Genetic Folding, Multi-Classification, Mercer's Rules

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