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用聚类-分类模式解决聚类问题
引用本文:周志勇,袁方,刘海博. 用聚类-分类模式解决聚类问题[J]. 广西师范大学学报(自然科学版), 2007, 25(2): 127-130
作者姓名:周志勇  袁方  刘海博
作者单位:河北大学,数学与计算机学院,河北,保定,071002;河北大学,数学与计算机学院,河北,保定,071002;河北大学,数学与计算机学院,河北,保定,071002
基金项目:河北省科技攻关计划资助项目(05213573),河北省教育厅科研计划资助项目(2004406)
摘    要:分类和聚类都是常用的数据挖掘方法,分类的优点是准确率较高,但需要带有类别标注的训练集;聚类不需要训练集,但准确率较低。提出一种聚类-分类模式来解决聚类问题,首先通过聚类方法自动形成训练集,然后在训练集的基础上进行分类操作。实验数据表明,提出的聚类-分类模式能够有效提高聚类的准确率。

关 键 词:聚类算法  分类算法  聚类-分类模式
文章编号:1001-6600(2007)02-0127-04
收稿时间:2006-11-15
修稿时间:2006-11-15

Clustering Based on Clustering-Classification Model
ZHOU Zhi-yong,YUAN Fang,LIU Hai-bo. Clustering Based on Clustering-Classification Model[J]. Journal of Guangxi Normal University(Natural Science Edition), 2007, 25(2): 127-130
Authors:ZHOU Zhi-yong  YUAN Fang  LIU Hai-bo
Affiliation:College of Mathematics and Computer Science,Hebei University,Baoding 071002,China
Abstract:Classification and clustering are both commonly used data mining methods.The advantage of classification is that the accuracy is higher,but the labeled training set is needed.The training set is not needed in clustering but the accuracy is lower.A clustering-classification model is proposed to solve the clustering problem.First,the training set is formed automatically by clustering,and then the classification proceeds based on the training set.Experiments show that the cluster-classification model can improve the effect of clustering.
Keywords:clustering  classification  clustering-classification model
本文献已被 CNKI 维普 万方数据 等数据库收录!
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