聊城大学学报：自然科学版2012，Vol.25Issue(2)：6-9,13,5.
基于SVM的决策树多类分类器及在遥感图像中的应用
Decision Tree Multi-class Classifiers Based on SVM and Applications to Remote Sensing Images
摘要
Abstract
In this paper, three kinds of decision tree multi-class classifiers based on SVM are pres- ented by means of three clustering methods, which are respectively clustering with minimum distance of class means, maximum distance of class means and maximum margin criteria. The experiments with AVIRIS remote sensing image are made for testing the validity and advantage of our proposed algo- rithms. The experimental results demonstrate that our methods are significantly better than minimum distance classification, linear discriminant classification, decision tree classification, OAR-SVM and OAO-SVM.关键词
支持向量机/决策树/聚类/最大间隔准则/AVIRIS遥感图像Key words
support vector machine/decision tree/clustering/maximum margin criterion/AVIRIS remote sensing image分类
数理科学引用本文复制引用
赵文嵩,马文慧,范丽亚..基于SVM的决策树多类分类器及在遥感图像中的应用[J].聊城大学学报：自然科学版,2012,25(2):6-9,13,5.基金项目
国家自然科学基金（10871226）和山东省自然科学基金（ZR2009AL006）资助项目 （）
