摘要
实现教育教学过程中对教师教学水平公正、准确、快速地评价,是学校实施现代化教学管理的重要前提,传统的教学评价方法存在着主观性大、精准度差以操作复杂等问题。本文提出了基于支持向量机的数据挖掘算法与学校教师的评价指标相结合的改进方案,利用SVM对样本数据进行分类,通过在评价系统中对样本数据的训练形成训练模型,并进一步利用该模型完成对预测数据的职能分析和评测。实验证明,同传统方法相比,方案具有综合性能优势及应用价值。
How to attain fair,accurate and fast evaluation of teacher in education and teaching,is an important premise of modern management in school.There exist some disadvantages as being subjective,poor accuracy and complex operation in traditional schemes.We proposed an improved method by combining data mining algorithm and the evaluation indicators of teachers.SVM is used to classify the sample data.Then we attain the training model through training the sample data in the evaluation system and take the intelligent evaluation and analysis on the prediction data with the training model.Our method is testified to have advantage in comprehensive performance and application value by experiments.
出处
《科技通报》
北大核心
2012年第8期221-223,共3页
Bulletin of Science and Technology
基金
河南省科技攻关项目(112102210233)
关键词
教学评价
SVM
惩罚因子
核函数
teaching evaluation
SVM
penalty factor
kernel function
