Welcome to the InfoSci Platform
Incremental Hyper-Sphere Partitioning for Classification

Incremental Hyper-Sphere Partitioning for Classification

Jinghao Song, Sheng-Uei Guan, Binge Zheng
Copyright: © 2014 |Volume: 5 |Issue: 2 |Pages: 17
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781466652408|DOI: 10.4018/ijaec.2014040105
Cite Article Cite Article

MLA

Song, Jinghao, et al. "Incremental Hyper-Sphere Partitioning for Classification." IJAEC vol.5, no.2 2014: pp.72-88. http://doi.org/10.4018/ijaec.2014040105

APA

Song, J., Guan, S., & Zheng, B. (2014). Incremental Hyper-Sphere Partitioning for Classification. International Journal of Applied Evolutionary Computation (IJAEC), 5(2), 72-88. http://doi.org/10.4018/ijaec.2014040105

Chicago

Song, Jinghao, Sheng-Uei Guan, and Binge Zheng. "Incremental Hyper-Sphere Partitioning for Classification," International Journal of Applied Evolutionary Computation (IJAEC) 5, no.2: 72-88. http://doi.org/10.4018/ijaec.2014040105

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

In this paper, an Incremental Hyper-Sphere Partitioning (IHSP) approach to classification on the basis of Incremental Linear Encoding Genetic Algorithm (ILEGA) is proposed. Hyper-spheres approximating boundaries to a given classification problem, are searched with an incremental approach based on a unique combination of genetic algorithm (GA), output partitioning and pattern reduction. ILEGA is used to cope with the difficulty of classification problems caused by the complex pattern relationship and curse of dimensionality. Classification problems are solved by a simple and flexible chromosome encoding scheme which is different from that was proposed in Incremental Hyper-plane Partitioning (IHPP) for classification. The algorithm is tested with 7 datasets. The experimental results show that IHSP performs better compared with those classified using hyper-planes and normal GA.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.