基于SVM的空间数据库的层次聚类分析

Support Vector Machine Based Hierarchical Clustering of Spatial Databases

支持向量机用于两类问题的识别研究 .本算法引入了 SVM,构造二叉树对多类问题进行层次聚类分析 .该算法采用 SVM对两类问题进行识别 ,通过合并逐步由底向上构造二叉树 ,最终二叉树的数目即为聚类数 .它适合任意形状的聚类问题 ,而且可以确定最优聚类的结果 ,并适于高维数据的分析 .

Support vector machine (SVM) is applied to recognize two separable classes. The algorithm builds up a binary tree to tackle multi class recognition by SVM based hierarchical clustering. SVM is used to recognize two classes and builds up a binary tree in a bottom to up version to analyze the multi class recognition. The number of binary trees is ultimately the number of clustering. It can be applied to clustering problems of arbitrary shapes, achieving the best result, and adapted to fit for the analysis of high dimensional data.