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| Incremental clustering algorithm via crossentropy | |
| 作者姓名： | Guan Tao Xu Jiucheng & Feng Boqin.State Key Laboratory of Intelligent Technology and Systems Dept. of Computer Science and Technology Tsinghua Univ. Beijing P. R. China .Coll. of Computer and Information Technology Henan Normal Univ. Xinxiang P. R. China .School of Electronics and Information Engineering Xi'an Jiaotong Univ. Xi'an P. R. China |
| 作者单位： | Guan Tao 1，3，Xu Jiucheng2 & Feng Boqin31.State Key Laboratory of Intelligent Technology and Systems，Dept. of Computer Science and Technology，Tsinghua Univ.，Beijing 100080，P. R. China;2.Coll. of Computer and Information Technology，Henan Normal Univ.，Xinxiang 453007，P. R. China;3.School of Electronics and Information Engineering，Xi'an Jiaotong Univ.，Xi'an 710049，P. R. China |
| 摘 要： | 1.INTRODUCTION Fuzzyclusteringisanunsupervisedwayofdatagrouping andusefulinpatternrecognition,informationretrieval,imageprocessing,faultdetection1,2].Itgroupsdatainto finiteclustersbyusingsomekindsofmeasuressuchasthe linearandnon lineardistance,theentropymeasure,or inclusiondegreeinfuzzyenvironments.Intermsofthe modelsandmeasuresbetweenobjects,differentalgo rithmspartitiondifferentdatasetsandproduceclusters withdifferentshapesandhavedistinctdifferenceintime andspaceefficiency.Currentclus… |
Incremental clustering algorithm via cross-entropy |
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| Guan Tao ,,Xu Jiucheng & Feng Boqin.State Key Laboratory of Intelligent Technology and Systems,Dept. of Computer Science and Technology,Tsinghua Univ.,Beijing ,P. R. China,.Coll. of Computer and Information Technology,Henan Normal Univ.,Xinxiang ,P. R. China,.School of Electronics and Information Engineering,Xi''''an Jiaotong Univ.,Xi''''an ,P. R. China.Incremental clustering algorithm via crossentropy[J].Journal of Systems Engineering and Electronics,2005,16(4). | |
| Authors: | Guan Tao Xu Jiucheng Feng Boqin |
| Institution: | 1. State Key Laboratory of Intelligent Technology and Systems,Dept. of Computer Science and Technology, Tsinghua Univ., Beijing 100080, P. R. China; School of Electronics and Information Engineering, Xi'an Jiaotong Univ., Xi'an 710049, P. R. China 2. Coll. of Computer and Information Technology, Henan Normal Univ., Xinxiang 453007, P. R. China 3. School of Electronics and Information Engineering, Xi'an Jiaotong Univ., Xi'an 710049, P. R. China |
| Abstract: | A new incremental clustering method is presented, which partitions dynamic data sets by mapping data points in high dimension space into low dimension space based on (fuzzy) crossentropy(CE). This algorithm is divided into two parts: initial clustering process and incremental clustering process. The former calculates fuzzy crossentropy or crossentropy of one point relative to others and a hierachical method based on crossentropy is used for clustering static data sets. Moreover, it has the lower time complexity. The latter assigns new points to the suitable cluster by calculating membership of data point to existed centers based on the crossentropy measure. Experimental comparisons show the proposed method has lower time complexity than common methods in the largescale data situations or dynamic work environments. |
| Keywords: | incremental clustering (fuzzy)crossentropy hierachical clustering |
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