PENG Xin-jun, WANG Yi-fei. CCH-Based Geometric Algorithms for SVM and the Applications[J]. Applied Mathematics and Mechanics, 2009, 30(1): 90-100.
Citation: PENG Xin-jun, WANG Yi-fei. CCH-Based Geometric Algorithms for SVM and the Applications[J]. Applied Mathematics and Mechanics, 2009, 30(1): 90-100.

CCH-Based Geometric Algorithms for SVM and the Applications

  • Received Date: 2008-08-26
  • Rev Recd Date: 2008-11-17
  • Publish Date: 2009-01-15
  • The support vector machine (SVM) is a novel machine learning tool in data mining. The geometric approach based on the compressed convex hull (CCH) with a mathematical framework is introduced to solve SVM classification problems. Compared with the reduced convex hull (RCH), CCH preserves the shape of geometric solid for the data set; meanwhile, it is easy to give the necessary and sufficient condition of determining its extreme points. As the practical applications of CCH, spare and probabilistic speed-up geometric algorithms were developed. Results of some numerical experiments show that the proposed algorithms can reduce the kernel evaluation and display nice performances.
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