id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_fyjswziacfg3pe4tfkp35fqd3q	Qiaolin Ye	Distance difference and linear programming nonparallel plane classifier	2011	3	.pdf	application/pdf	1976	262	67	We first propose Distance Difference GEPSVM (DGEPSVM), a binary classifier that obtains two nonparallel Moreover, the proposed algorithm gives classification correctness comparable to that of LSTSVM and TWSVM, but with lesser unknown parameters. of very large sparse datasets (Guarracino, Cifarelli, Seref, & Pardalos, 2007) such as generalized proximal SVM (GEPSVM for short) GEPSVM obtains each of the nonparallel planes by solving the eigenvector corresponding to a smallest lower computational complexity and its better classification performance in terms of solving XOR problems with respect to standard SVM that find one plane that separates the two classes. algorithms obtain two planes by solving generalized eigenvalue Recently, a twin SVM algorithm (TWSVM for short), proposed by show the effectiveness of TWSVM over SVM and GEPSVM (Arun http://www.elsevier.com/locate/eswa LSTSVM in terms of solving XOR examples with different distribution and gives comparable classification correctness on standard TWSVM has different formulation from GEPSVM.	./cache/work_fyjswziacfg3pe4tfkp35fqd3q.pdf	./txt/work_fyjswziacfg3pe4tfkp35fqd3q.txt