计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (12): 191-193.
• 工程与应用 • 上一篇 下一篇
高峰
收稿日期:
修回日期:
出版日期:
发布日期:
通讯作者:
Received:
Revised:
Online:
Published:
摘要: 考虑不同出现频率的可分类属性值对聚类中心的影响,通过重新定义聚类中心和距离,提出一种新的聚类算法K- centers,这种算法能够有效处理可分类和混合类型数据。在此基础上,将K-centers应用于课程教学评估,分析不同类型课程的特点,为评估教学提供了参考。
关键词: 聚类分析, K-centers, 混合类型, 教学评估
Abstract: Considering the effect of attribute values with different frequencies on clustering centers and applying a new centroid and distance measurement, a hard and fuzzy K-centers clustering algorithm is proposed to handle mixed-type data sets. Moreover,the algorithm is used to cluster different teaching courses and analyze the teaching characteristics of the courses in a university,which help improve teaching management.
Key words: cluster analysis, K-centers, hybrid category, teaching evaluation
高峰. K-centers聚类算法在教学评估中的应用[J]. 计算机工程与应用, 2007, 43(12): 191-193.
0 / 推荐
导出引用管理器 EndNote|Ris|BibTeX
链接本文: http://cea.ceaj.org/CN/
http://cea.ceaj.org/CN/Y2007/V43/I12/191