Title :
A comparison of consensus- and critical point-based classification strategies
Author :
Weichao Xu ; Rubao Ma ; Qinruo Wang
Author_Institution :
Sch. of Autom., Guangdong Univ. of Technol., Guangzhou, China
Abstract :
In this paper we compare the consensus-based strategy (CBS) and the critical point-based strategy (CPBS) which are commonly adopted in the practice of designing classifiers. Theoretical analyses and simulation results reveal the close relationship between the kurtosis (long tailedness) of the distribution of data patterns and the performance of SVM designed with CPBS. Monte Carlo simulation results agree with the theoretical findings.
Keywords :
Monte Carlo methods; pattern classification; support vector machines; CBS; CPBS; Monte Carlo simulation; SVM; classifier design; consensus-based classification strategy; critical point-based classification strategy; data pattern distribution; kurtosis; support vector machines; Educational institutions; Gaussian distribution; Monte Carlo methods; Random variables; Simulation; Support vector machines; Training; Bernoulli distribution (BD); Consensus-based strategy (CBS); Critical point-based strategy (CPBS); Fisher linear discrimination analysis (FLDA); Laplace distribution (LD); Normal distribution (ND); Support vector machine (SVM); Uniform distribution (UD);
Conference_Titel :
Computational Intelligence and Cybernetics (CyberneticsCom), 2012 IEEE International Conference on
Conference_Location :
Bali
Print_ISBN :
978-1-4673-0891-5
DOI :
10.1109/CyberneticsCom.2012.6381616
