基于支持向量机的教学质量评价研究  

TEACHING QUALITY EVALUATION BASED ON SUPPORT VECTOR MACHINE

作　　者：朱海林[1] 宋承祥[2] 刘弘[1] 何鲁青 

机构地区：[1]山东师范大学信息科学与工程学院,济南250014 [2]山东省教育厅,济南博士生导师250014 [3]山东泉清通信有限责任公司,济南250101

出　　处：《山东师范大学学报（自然科学版）》2008年第4期4-6,共3页Journal of Shandong Normal University(Natural Science)

基　　金：国家自然科学基金资助项目(60374054);山东省高等学校教学改革立项项目(编号C05074)支持

摘　　要：支持向量机是一种新的机器学习算法,由于出色的学习性能,以及在小样本识别等许多方面有其独特的优势,现已应用在许多领域.目前,高校对教学质量越发重视,如何客观、准确、方便地评价教学质量是一个值得研究的课题.结合目前教学质量评价研究现状,提出了一个基于SVM的评价模型,经检验该模型能够获得较为理想的评价结果.Support Vector Machine is a new machine learning algorithm, as its excellent performance of the study, and to identify many ways in small samples, which is now used in many areas. Currently, colleges and universities pay more attention to the quality of teaching. How to evaluate the quality of teaching objectively, aecurarely, and conveniently is a subject worth studying. At present, combined with the research of teaching quality evaluation, an evaluation model based on SVM is made, and the model is tested to obtain better results.

关 键 词：支持向量机 教学评价 研究 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]