登录 | 注册 | 充值 | 退出 | 公司首页 | 繁体中文 | 满意度调查
综合馆
基于EMD距离的多示例聚类
  • 摘要

    多示例学习中,包由多个示例组成,有明确标记,而示例标记却不确定.已有聚类研究都针对单示例、单标记,因而无法直接应用于多示例问题.基于推土机距离(earth mover's distance,EMD)提出了一种新的多示例聚类算法ECMIL.该方法首先利用欧式距离计算包内示例相似度,将相似示例合并;然后将需要度量距离相似性的包内示例分别看作供货者和消费者,计算货物拥有量和货物需求量;对推土机距离无法供货问题,通过增大满足条件供货者的权值加以解决;最后使用k-medoids算法进行聚类.在基准数据集MUSK,Corel和SIVAL上进行实验,表明ECMIL算法是有效的.

  • 作者

    李展  彭进业  温超  LI Zhan  PENG Jin-ye  WHEN Chao 

  • 作者单位

    西北大学信息科学与技术学院,西安,710069/西北大学信息科学与技术学院,西安710069;西北工业大学电子信息学院,西安710072

  • 刊期

    2011年7期 ISTIC PKU

  • 关键词

    多示例聚类  推土机距离  k-medoids 

参考文献
  • [1] 张霞,王素贞,尹怡欣,赵海龙. 基于模糊粒度计算的K-means文本聚类算法研究. 计算机科学, 2010,2
  • [2] 路晶,马少平. 基于多例学习的Web图像聚类. 计算机研究与发展, 2009,9
  • [3] 路晶,马少平. 基于多例学习的Web图像聚类. 计算机研究与发展, 2009,9
  • [4] MIN-LING ZHANG;ZHI-HUA ZHOU. Adapting RBF Neural Networks to Multi-Instance Learning. Neural processing letters, 2006,1
  • [5] Rubner Y.;Guibas LJ.;Tomasi C.. The Earth Mover's Distance as a metric for image retrieval. International Journal of Computer Vision, 2000,2
  • [6] Zhang, Min-Ling;Zhou, Zhi-Hua. Multi-instance clustering with applications to multi-instance prediction. Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies, 2009,1
  • [7] Yixin Chen;Jinbo Bi;Wang J.Z.. MILES: Multiple-Instance Learning via Embedded Instance Selection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006,12
  • [8] Dietterich T G;Lathrop R H;Lozano-Pérez T. Solving the multiple instance problem with axis-parallel rectangles. Artificial Intelligence, 1997,12
  • [9] Zhang Dan;Wang Fei;Si Luo. M3IC:Maximum Margin Multiple Instance Clustering. 2009
  • [10] Maron O;Lozano-Pérez T. A framework for multiple-instance learning. 1998
  • [11] Chevaleyre Y;Zucker J-D. Solving multiple-instance and multiple-part learning problems with decision trees and decision rules.Application to the mutagenesis problem. 2001
  • [12] Wang Jun;Zucker J-D. Solving the multiple-instance problem:a lazy learning approach. 2000
  • [13] Stuart A;Thornas H;Ioannis T. Multiple instance learning with generalized support vector machines. 2002
  • [14] Zhou Zhi-hua;Xu Jun-ming. On the relation between multi-instance On the relation between multi-instance learning and semisupervised learning. 2007
  • [15] Kwok J T;Cheung P-M. Marginalized multi-instance kernels. Hydrabad,India, 2007
  • [16] Zhou Z-H;Sun Y-Y;Li Y-F. Multi-instance learning by treating instances as non-I.I.D.samples. 2009
  • [17] Chen Yi-xin;Wang J Z. Image categorization by learning and reaoning with regions. Journal of Machine Learning Research, 2004,08
  • [18] Kim M;De la Torre F. Gaussian Processes Multiple Instance Learning. 2010
  • [19] Deselaers T;Ferrari V. A Conditional Random Field for Multiple-Instance Learning. 2010
  • [20] Wei Ping;Ye Xu;Non-I.I.D. Multi-Instance Dimensionality Reduction by Learning a Maximum Bag Margin Subspace. 2010
  • [21] Sun Yu-yin;Ng M K;Zhou Zhi-hua. Multi-Instance Dimensionality Reduction. 2010
  • [22] Zhang Q;Yu W;Goldman S A. Content-based image retrieval using multiple-instance learning. 2002
  • [23] Settles B;Craven M;Ray S. Multiple instance active learning. 2008
  • [24] Ruffo G. Learning single and multiple instance decision trees for computer security applications Doctoral dissertation. Torino,Italy:CS Dept.,Univ.Turin, 2000
  • [25] Zhang C;Viola P. Multiple-instance pruning for learning efficient cascade detectors. 2008
  • [26] Fung G;Dundar M;Krishnappuram B. Multiple instance learning for computer aided diagnosis. 2007
查看更多︾
相似文献 查看更多>>
18.206.15.215