上下文决策树学习算法及其在机械波图像中的应用  

Context-based decision tree learning algorithm and its application in images of mechanical wave

作　　者：许晴[1] 李凡长[1] 

机构地区：[1]苏州大学计算机科学与技术学院,江苏苏州215006

出　　处：《合肥工业大学学报（自然科学版）》2013年第2期160-164,共5页Journal of Hefei University of Technology：Natural Science

基　　金：国家自然科学基金资助项目(61033013;60775045)

摘　　要：机器学习技术在现代各种数据分析中是备受关注的有效方法之一,目前已在众多领域得到广泛应用。文章以目前较为流行的决策树学习为重点,介绍了决策树学习的几个较为成熟的算法,并将相应算法应用到机械波图像分析中,提出了5点、7点与11点上下文决策树学习算法。通过实验验证该处理方法是有效的。Machine learning technique is an effective way of modern data analysis. It has been widely used in many fields and got a lot of attention. Focusing on the most popular decision tree learning, a few of the most sophisticated algorithms are introduced. Then the corresponding algorithm is applied to the image analysis of the mechanical wave, and the five-point, seven-point and eleven-point context- based decision tree learning algorithms are proposed. The approach is proved to be meaningful by ex- perimental validation.

关 键 词：决策树 信息熵 信息增益 机械波图像 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]