关键词: 类均值, 步长优化, 权重, 交叉验证

Abstract: In order to improve the classification accuracy of traditional nearest neighbor classification based on local mean and class mean（LMS）, it is necessary to study the weights allocation of class mean. The paper uses objective decision-making information to determine the weight of class mean as a mathematical formula. The simultaneous method with step size optimization techniques obtains a more appropriate distance weighting. A large amount of experiments by the UCI dataset show that the improved algorithm prevails over traditional LMS algorithm in classification effect.

Key words: class mean, step size optimization, weight, cross-validation