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College teachers subhealth decision analyzing by using improved association rules

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成果类型:
期刊论文、会议论文
作者:
Qin, Feng-Zhen*
通讯作者:
Qin, Feng-Zhen
作者机构:
[Qin, Feng-Zhen] Cent China Normal Univ, Dept Phys Educ, Wuhan 430079, Hubei, Peoples R China.
通讯机构:
[Qin, Feng-Zhen] C
Cent China Normal Univ, Dept Phys Educ, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
关键词:
constitution data;subhealthy;data mining;aprior
期刊:
Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
年:
2008
卷:
6
页码:
3540-3544
会议名称:
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
会议论文集名称:
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)论文集
会议时间:
2008-07-12
会议地点:
昆明
会议赞助商:
河北大学
机构署名:
本校为第一且通讯机构
院系归属:
物理科学与技术学院
体育学院
摘要:
With the high development of science and technology, the progresses of society, the increasing pressure of modern work, the trend of people's health states is dropping gradually. The number of people in subhealthy state is enlarging day by day. Many researchers have done a lot of researches on the constitution health data of college teachers by traditional math analyzing method. Some superficial information is obtained easily though traditional query operation from constitution data, but deep level information that hides in the constitution data is difficult to be discovered. Based on it, an i...

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