| 最优特征子集选择问题 |
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| 引用本文： | 陈彬 洪家苯. 最优特征子集选择问题[J]. 计算机学报, 1997, 20(2): 133-138 |
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| 作者姓名： | 陈彬 洪家苯 |
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| 作者单位： | 哈尔滨工业大学计算机科学与工程系 |
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| 摘 要： | 机器学习和模式识别面临的一个重要问题，就是特征子集的选择问题，即从一个大的已生征特集合，选择一个子集合来一致地描述已知例。特别，最优特征子集选择问题，即最小的特征子集问题的 计算杂性至今学不清楚。
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| 关 键 词： | 机器学习 模式识别 特征子集选择 |
THE PROBLEM OF FINDING OPTIMAL SUBSET OF FEATURES |
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| CHEN Bin, HONG Jiarong, WANG Yadong. THE PROBLEM OF FINDING OPTIMAL SUBSET OF FEATURES[J]. Chinese Journal of Computers, 1997, 20(2): 133-138 |
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| Authors: | CHEN Bin HONG Jiarong WANG Yadong |
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| Abstract: | Machine learning and pattern recognition are confronted with the difficulty in selecting subset of features. That is,from a large set of candidate features, selecting a subset of features which are able to represent given examples (samples) consistently. Especially,the problem of finding an optimal subset of features has remained open. This paper, proves that the problem of finding an optimal subset of features is NP-hard, and presents a heuristic algorithm to solve this problem. |
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| Keywords: | Machine learning pattern recognition feature subset selection set covering NP-hardness greedy-algorithm. |
| 本文献已被 CNKI 维普 等数据库收录！ |
