基于属性相似度的云分类器

Cloud Classifier Based on Attribute Similarity

提出了属性相似度概念解决高维对象分类的权重问题,并结合云理论建立了基于属性相似度的云分类器.采用云理论建立训练集的各属性模型,表达各属性值隶属于其类别中心Ex的程度.分类模型由属性模型集成得到,属性权重根据属性相似度计算.各类别的同一属性间的相似度越大,此属性对分类的作用越小.基于粒子群优化方法对分类模型的中心位置Ex进行优化.将此分类器与普通云分类器应用于iris数据集的分类实验,该分类器的分类效果好于后者.

<Abstrcat> The concept of attribute similarity is presented to solve the weight problem of multi-dimension object classification, and cloud classifier based on attributes similarity is presented also. Every attribute model of training set is set up by cloud model, which describes the membership to which any an attribute value belongs its class center Ex. Classification model is integrated by every attribute model, and attribute weight is calculated by attribute similarity. The larger the similarity of an attribute, the smaller the action of the attribute to classification is. The center of classifier is optimized by particle swarm optimization algorithm. The classifier is used in classifying iris data set, its classification result is better than that of the common cloud model.