|
|||||
|
|
| 针对不确定正例和未标记学习的最近邻算法(英文) | |
| 引用本文： | 潘世瑞,张阳,李雪,王勇. 针对不确定正例和未标记学习的最近邻算法(英文)[J]. 计算机科学与探索, 2010, 4(9): 769-779. DOI: 10.3778/j.issn.1673-9418.2010.09.001 |
| 作者姓名： | 潘世瑞 张阳 李雪 王勇 |
| 作者单位： | 1. 西北农林科技大学,信息工程学院,陕西,杨凌,712100 2. 西北农林科技大学,信息工程学院,陕西,杨凌,712100;南京大学,计算机软件新技术国家重点实验室,南京,210093 3. 昆士兰大学,计算机及电子工程系,布里斯班,4072,澳大利亚 4. 西北工业大学,计算机学院,西安,710072 |
| 基金项目： | 国家自然科学基金，中央高校基本科研业务费专项资金 |
| 摘 要： | 研究了在正例和未标记样本场景下不确定样本的分类问题,提出了一种新的算法NNPU(nearest neighbor algorithm for positive and unlabeled learning)。NNPU具有两种实现方式:NNPUa和NNPUu。在UCI标准数据集上的实验结果表明,充分考虑数据不确定信息的NNPUu算法要比仅仅考虑样本中不确定信息均值的NNPUa算法具有更好的分类能力;同时,NNPU算法在对精确数据进行分类时,比NN-d、OCC以及aPUNB算法性能更优。 |
| 关 键 词： | 不确定数据 正例和未标记样本学习 最近邻算法 |
| 修稿时间： | |
Nearest Neighbor Algorithm for Positive and Unlabeled Learning with Uncertainty |
|
| PAN Shirui,ZHANG Yang,LI Xue,WANG Yong. Nearest Neighbor Algorithm for Positive and Unlabeled Learning with Uncertainty[J]. Journal of Frontier of Computer Science and Technology, 2010, 4(9): 769-779. DOI: 10.3778/j.issn.1673-9418.2010.09.001 | |
| Authors: | PAN Shirui ZHANG Yang LI Xue WANG Yong |
| Affiliation: | 1. College of Information Engineering, Northwest A&;F University, Yangling, Shaanxi 712100, China 2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China 3. School of Information Technology and Electrical Engineering, University of Queensland, Brisbane 4072, Australia 4. School of Computer, Northwestern Polytechnical University, Xi’an 710072, China |
| Abstract: | This paper studies the problem of uncertain data classification under positive and unlabeled (PU) learning scenario. It proposes a novel algorithm, NNPU (nearest neighbor algorithm for positive and unlabeled learning), to handle this problem with two varieties, NNPUa and NNPUu. Experimental results on benchmark UCI datasets show that NNPUu, which considers the whole uncertain information on the datasets, has a better ability to classify unseen examples than NNPUa that considers the average value of uncertainty only. Furthermore, NNPU outperforms some existing algorithms such as NN-d, OCC (one-class classifier) and aPUNB in handling precise data. |
| Keywords: | uncertain data positive and unlabeled learning nearest neighbor algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
| 点击此处可从《计算机科学与探索》浏览原始摘要信息 | |
| 点击此处可从《计算机科学与探索》下载免费的PDF全文 | |
