| 小样本机器学习算法的特性分析与应用 |
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| 引用本文： | 辛宪会,叶秋果,滕惠忠,郭思海,李军,张靓,韩晓宏.小样本机器学习算法的特性分析与应用[J].海洋测绘,2007,27(3):16-19. |
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| 作者姓名： | 辛宪会 叶秋果 滕惠忠 郭思海 李军 张靓 韩晓宏 |
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| 作者单位： | 海军海洋测绘研究所 天津300061 |
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| 摘 要： | 基于经典统计学的机器学习算法,在解决小样本学习问题时表现得不能令人满意。在总结分析小样本机器学习算法特点的基础上,以支持向量机(SVM)学习算法为例,定量分析了影响其泛化性能、学习性能的几个因素,实验结果与理论分析结论取得了良好的一致性;SVM用于解决KTH-TIPS纹理图像分类问题,取得了很好的实验结果。
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| 关 键 词： | 图像处理 机器学习 统计学习理论 支持向量机 纹理图像 |
| 文章编号： | 1671-3044（2007）03-0016-04 |
| 修稿时间： | 2006-07-262007-01-18 |
Applications and Analysis for the Features of the Machine Learning Algorithm with Limited Samples |
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| XIN Xian-hui,YE Qiu-guo,TENG Hui-zhong,GUO Si-hai,LI Jun,ZHANG Liang,HAN Xiao-hong.Applications and Analysis for the Features of the Machine Learning Algorithm with Limited Samples[J].Hydrographic Surveying and Charting,2007,27(3):16-19. |
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| Authors: | XIN Xian-hui YE Qiu-guo TENG Hui-zhong GUO Si-hai LI Jun ZHANG Liang HAN Xiao-hong |
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| Institution: | Naval Institute of Hydrographic Surveying and Charting,Tianjin,300061 |
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| Abstract: | Some limitation of the machine learning algorithm based on the classical statistics has been displayed when it is used to solve the learning problems with limited samples.On the foundation of summarizing their characteristics,the quantitative analysis for generalization function and learning function are presented in this paper,taking example for the support vector machine(SVM) algorithm.The consistency between experimental result and theoretical conclusion is perfect,and a favorable classification result has been gained when SVM is used to KTH-TIP texture images. |
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| Keywords: | image processing machine learning statistical learning theory support vector machine texture image |
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