基于分形理论的多尺度分类尺度上推算法  

Scaling-up Algorithm of Multi-scale Classification Based on Fractal Theory

作　　者：李佳星 赵书良[1,2] 安磊 李长镜[1,2] LI Jia -xing, ZHAO Shu- liang ,AN Lei, LI Changjing(1College of Mathematic ＆ Information Science, Hebei Normal University,Shijiazhuang 050024 ,China ;2Hebei Key Laboratory of Computational Mathematics ＆ Applications, Hebei Normal University,Shijiazhuang 050024,Chin)

机构地区：[1]河北师范大学数学与信息科学学院,石家庄050024 [2]河北师范大学河北省计算数学与应用重点实验室,石家庄050024

出　　处：《计算机科学》2018年第B06期453-459,共7页Computer Science

基　　金：国家自然科学资金项目(71271067);国家社科基金重大项目(13&ZD091);河北省高等学校科学技术研究项目(QN2014196);河北师范大学硕士基金(xj2015003)资助

摘　　要：目前,多尺度数据挖掘的研究多集中于空间图像数据,在一般数据集上的研究已经初见成果,主要包括多尺度聚类以及多尺度关联规则,但还没有研究涉及一般数据下的分类。结合分形理论思想,将多尺度数据挖掘相关理论、知识和方法应用于分类领域,提出基于豪斯多夫距离(HD)的相似性度量方法;相对于以往对权重的经验定义,文中明确通过广义分形维数的相似性定义权重来提高相似性度量方法的精度;提出多尺度分类尺度上推算法(MultiScale Classification Scaling-Up Algorithm,MSCSUA);实验采用4个UCI基准数据集和1个真实数据集(H省部分人口)进行仿真实验,实验结果表明多尺度分类思想可行有效,并且MSCSUA算法在不同数据集上的性能均优于SLAD,KNN,Decision Tree以及LIBSVM算法。At present,the research of multi-scale data mining mainly focuses on space image data,and recently has produced some results on the general data,including the multi-scale clustering and multi-scale association rules,but it has not been involved in the field of classification mining.Combining with fractal theory,this paper applied the theory,knowledge and methods related to the multi-scale data mining to the areas of the classification mining,and proposed an approach of similarity measure based on Hausdorff.Relative to the definition of weight through experience,this paper clearly defined it by the similarity of generalized fractal dimension to improve the precision of similarity measure.Then,this paper proposed a multi-scale classification scaling-up algorithm named MSCSUA（Multi-Scale Classification ScalingUp Algorithm）.At last,this paper performed experiments on four UCI benchmark data sets and one real data set（H province part of the population）.The experimental results show that the thought of multi-scale classification is feasible and effective,the MSCSUA algorithm performs well in terms of classification than SLAD,KNN,Decision Tree and LIBSVM algorithms on different data sets.

关 键 词：多尺度数据挖掘 多尺度分类 分形理论 尺度上推 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]