| 知识发现中缺损数据的处理(II) |
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| 引用本文： | 卫金茂,黄道.知识发现中缺损数据的处理(II)[J].华东理工大学学报(自然科学版),2000,26(5):521-524. |
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| 作者姓名： | 卫金茂 黄道 |
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| 作者单位： | 华东理工大学自动化研究所!上海200237 |
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| 基金项目： | 国家“8 63”高技术项目基金!资助 ( 863- 511- 84 5- 0 0 7) |
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| 摘 要： | 研究了在知识发现过程中处理连续取值属性值缺损的问题。提出了进行连续值划分的“超长方体”划分法。在此基础上 ,通过发现值缺损属性的取值集合 ,值缺损属性是否为强作用属性以及与其他属性是否相关 ,解决了对含有缺损数据的信息源进行知识发现的问题。文中通过处理UCI机器学习数据库中的 COIL数据库 ,说明了本方法是可行的。
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| 关 键 词： | 知识发现 属性相关 强作用属性 缺损数据 |
| 修稿时间： | 2000-04-24 |
Dealing
with Imperfect Information in Knowledge Discovery (II) |
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| WEI Jin mao,HUANG Dao.Dealing
with Imperfect Information in Knowledge Discovery (II)[J].Journal of East China University of Science and Technology,2000,26(5):521-524. |
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| Authors: | WEI Jin mao HUANG Dao |
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| Institution: | WEI Jin mao,HUANG Dao * |
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| Abstract: | The problem of dealing with imperfect information in knowledge discovery is further studied in this paper. A hypercuboid approach using over lapping feature intervals for partitioning continuous value into intervals is presented. Efforts have been made to find the set of values which the attributes with incomplete value may take and to determine whether the attributes are of strong effect or correlated with others, resulting in a satisfactory solution to such a problem. |
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| Keywords: | knowledge discovery correlated attribute strong effect attribute imperfect information |
| 本文献已被 CNKI 等数据库收录！ |
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