The Research on Newly Improved Bound Semi-supervised Support Vector Machine Learning Algorithm

SVM is the structural risk minimization of statistical learning theory developed on the basis of a pattern recognition method, based on limited sample information and the complexity of the model to find the best compromise between the generalization ability. As there is a supervised learning method, the standard SVM classification requires supervised learning algorithm based on the principle: from a limited number of labeled samples to learn the rules and the rule extended to the unknown non-tag samples.