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基于多维自组织特征映射的聚类算法研究
引用本文:江波,张黎.基于多维自组织特征映射的聚类算法研究[J].计算机科学,2008,35(6):181-182.
作者姓名:江波  张黎
作者单位:贺州学院计算机科学与工程系,贺州,542800
摘    要:作为神经网络的一种方法,自组织特征映射在数据挖掘、模式分类和机器学习中得到了广泛应用.本文详细讨论了自组织特征映射的聚类算法的工作原理和具体实现算法.通过系统仿真实验分析,SOFMF算法很好地克服了许多聚类算法存在的问题,在时间复杂度上具有良好的性能.

关 键 词:组织特征映射  聚类  数据挖掘  神经网络

Study of Algorithms of Clustering Based on Multi-dimensional Self-organizing Feature Mapping
JIANG Bo,ZHANG Li.Study of Algorithms of Clustering Based on Multi-dimensional Self-organizing Feature Mapping[J].Computer Science,2008,35(6):181-182.
Authors:JIANG Bo  ZHANG Li
Affiliation:JIANG Bo,ZHANG Li (Department of Computer Science and Engineering,Hezhou University,Hezhou,China
Abstract:As a method of neural network,the self-organizing feature mapping(SOFM) is an excellent approach for data mining, pattern classification and machine learning. The theory and algorithm of SOFM are discussed in detail in this article. Simultaneously analyze and summarize this algorithm: overcome the insufficiency of many clustering algorithms, be able to find clusters in different shapes, be non-sensitive to the input data sequence, process noise data and multi-dimensional data well, and have multi-resolution...
Keywords:Self-organizing feature mapping  Clustering  Data mining  Neural network  
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