关键词: 最小最大概率机, Boosting, 信息增益, 特征加权

Abstract: It constructs a Feature Weighted MPM（FWMPM） based on the Boosting. It estimates the relative importance of each feature by computing the Boosted distance. It is also the weight of each feature. It makes use of the weights for computing the inner product and Euclidean distance in kernel functions. In this way the MPM can allay the influence of trivial relevant feature. The experimental results and analysis show that the FWMPM has the better performance of class than the standard MPM.

Key words: Minimax Probability Machine（MPM）, Boosting, information gain, feature weighting