关键词: 支持向量机, 后验概率, 统计学习理论

Abstract: Support vector machine is a new classification algorithm based on statistical learning theory. After the discussion of the current multiclass SVMs, a novel multiclass SVM classifier based on geometric distance was proposed. The Posterior probability output of binary SVM was generalized to multiclass SVM. Without iteration computing, this method improved prediction accuracy with fast computing. The numeric experiments prove that above two methods have good generalization, which can increase prediction accuracy to unknown examples.

Key words: Support Vector Machine(SVM), posterior probability, statistical learning theory