JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (6): 15-22.doi: 10.6040/j.issn.1672-3961.1.2016.019

Previous Articles     Next Articles

Neighborhood related multiple-instance classifiers based on integrated Hausdorff distance

CHEN Zehua, SHANG Xiaohui, CHAI Jing   

  1. College of Information Engineering, Taiyuan University of Technology, Taiyuan 030024, Shanxi, China
  • Received:2016-07-12 Online:2016-12-20 Published:2016-07-12

PDF (PC)

555

Abstract: Based on the analysis of minimal Hausdorff(minH)and maximal Hausdorff(maxH)distances, integrated Hausdorff(intH)distance was proposed to combine minH and maxH, and used to design neighborhood related multiple-instance classifiers. The Neighborhood Component Analysis(NCA)model was used to learn the weighting coefficients in intH automatically and obtain the optimal intH according to the neighborhood related classification criterion. The experimental results showed that in most cases, compared with minH and maxH, intH could improve the classification accuracies of neighborhood related multiple-instance classifiers.

Key words: multiple-instance learning, weighting coefficients, Hausdorff distance, classifier, neighborhood component analysis

CLC Number: 

  • TP181
[1] 周志华. 多示例学习[M]. 知识科学中的基本问题研究. 北京:清华大学出版社, 2006:322-336.
[2] DIETTERICH T G, LATHROP R H, LOZANO-PEREZ T. Solving the multiple-instance problem with axis-parallel rectangles[J]. Artificial Intelligence, 1997, 89(1-2): 31-71.
[3] MARON O. Learning from ambiguity[D]. Boston: Massachusetts Institute of Technology, 1998.
[4] MARON O, LOZANO-PEREZ T. A framework for multiple-instance learning[C] //Advances in Neural Information Processing Systems 10. Denver, USA: MIT Press, 1998:570-576.
[5] ZHANG Q, GOLDMAN S A. EM-DD: an improved multiple-instance learning technique[C] //Advances in Neural Information Processing Systems 14. Vancouver, Canada: MIT Press, 2002:1073-1080.
[6] WANG J, ZUCKER J D. Solving the multiple-instance problem: a lazy learning approach[C] //Proceedings of the 17th International Conference on Machine Learning. Stanford, USA: Morgan Kaufmann Press, 2000:1119-1125.
[7] ANDREWS S, TSOCHANTARIDIS I, HOFMANN T. Support vector machines for multiple-instance learning[C] //Advances in Neural Information Processing Systems. Vancouver, Canada: MIT Press, 2003:561-568.
[8] GARTER T, FLACH P A, KOWALCZYK A, et al. Multi-instance kernels[C] //Proceedings of the 19th International Conference on Machine Learning. Sydney, Australia: Morgan Kaufmann Press, 2002:179-186.
[9] ZHOU Zhihua, SUN Yuyin, LI Yufeng. Multi-instance learning by treating instances as non-I.I.D. samples[C] //Proceedings of the 26th International Conference on Machine Learning. Montreal, Canada: ACM Press, 2009:1249-1256.
[10] LI W J, YEUNG D T. MILD: multiple-instance learning via disambiguation[J]. IEEE Transactions on Knowledge and Data Engineering, 2010, 22(1):76-89.
[11] SUN Y Y, NG M K, ZHOU Z H. Multi-instance dimensionality reduction[C] //Proceedings of the 24th AAAI Conference on Artificial Intelligence. Atlanta, USA: AAAI Press, 2010: 587-592.
[12] PING Wei, XU Ye, REN Kexin, et al. Non-i.i.d. multi-instance dimensionality reduction by learning a maximum bag margin subspace[C] //Proceedings of the 24th AAAI Conference on Artificial Intelligence Atlanta. USA: AAAI Press, 2010: 551-556.
[13] AMAR R A, DOOLY D R, GOLDMAN S A, et al. Multiple-instance learning of real-valued data[C] //Proceedings of the 18th International Conference on Machine Learning. Williamstown, USA: Morgan Kaufmann Press, 2001: 3-10.
[14] 薛晓冰,韩洁凌,姜远,等. 基于多示例学习技术的 Web 目录页面链接推荐[J].计算机研究与发展, 2007,44(3):406-411. XUE Xiaobing, HAN Jieling, JIANG Yuan, et al. Link recommendation in web index page based on multi-instance learning techniques[J]. Journal of Computer Research and Development, 2007, 44(3):406-411.
[15] ROWEIS S, HINTON G, SALAKHUTDINOV R. Neighbourhood component analysis[C] //Advances in Neural Information Processing Systems. Vancouver, Canada: MIT Press, 2005:513-520.
[16] PRESS W H, TEUKOLSKY S A, VETTERLING W T, et al. Numerical recipes: the art of scientific computing[M]. New York: Cambridge University Press, 2007.
[17] ZHANG Minling, ZHOU Zhihua. Multi-instance clustering with applications to multi-instance prediction[J]. Applied Intelligence, 2009, 31(1):47-68.
[18] ZAFRA A, PECHENIZKIY M, VENTURA S. ReliefF-MI: an extension of ReliefF to multiple instance learning[J]. Neurocomputing, 2012, 75(1):210-218.
[1] WANG Yuou, YUAN Yingchun, HE Zhenxue, WANG Kejian. A relation extraction method based on improved RoBERTa, multiple-instance learning and dual attention mechanism [J]. Journal of Shandong University(Engineering Science), 2025, 55(2): 78-87.
[2] Xiaoxiong HOU,Xinzheng XU,Jiong ZHU,Yanyan GUO. Computer aided diagnosis method for breast cancer based on AlexNet and ensemble classifiers [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 74-79.
[3] Hongbin ZHANG,Diedie QIU,Renzhong WU,Tao ZHU,Jin HUA,Donghong JI. Image attribute annotation based on extreme gradient boosting algorithm [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 8-16.
[4] Lianming MOU. Weighted k sub-convex-hull classifier based on adaptive feature selection [J]. Journal of Shandong University(Engineering Science), 2018, 48(5): 32-37.
[5] JIANG Weijian1,2, GUO Gongde1,2*, LAI Zhiming1,2. An improved adaboost algorithm based on new Haar-like feature for face detection [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2014, 44(2): 43-48.
[6] ZHAO Jia-min, FENG Ai-min*, LIU Xue-jun. A new structured one-class support vector machine with local density embedding [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2012, 42(4): 13-18.
[7] LI Yu-jian, MENG Dong-xia*, GUI Zhi-ming. Fast computation of characteristic boundary points for improving geometric ensembles [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(4): 56-60.
[8] GUO Jian-yi1,2, LEI Chun-ya1, YU Zheng-tao1,2, SU Lei1,2, ZHAO Jun1, TIAN Wei1. A semi-supervised learning method based on information entropy to extract the domain entity relation [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2011, 41(4): 7-12.
[9] FENG Ai-min1, LIU Xue-jun1, CHEN Bin2. Structure large margin one-class classifier [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(3): 6-12.
[10] . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 6-14.
[11] CHEN Tao,FANG Zhi-gang,XU Jie . A multi-channel identity verification system based on face and voice [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(2): 56-60 .
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] LI Kan . Empolder and implement of the embedded weld control system[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 37 -41 .
[2] SHI Lai-shun,WAN Zhong-yi . Synthesis and performance evaluation of a novel betaine-type asphalt emulsifier[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 112 -115 .
[3] LAI Xiang . The global domain of attraction for a kind of MKdV equations[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 87 -92 .
[4] YU Jia yuan1, TIAN Jin ting1, ZHU Qiang zhong2. Computational intelligence and its application in psychology[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 1 -5 .
[5] CHEN Rui, LI Hongwei, TIAN Jing. The relationship between the number of magnetic poles and the bearing capacity of radial magnetic bearing[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(2): 81 -85 .
[6] WANG Bo,WANG Ning-sheng . Automatic generation and combinatory optimization of disassembly sequence for mechanical-electric assembly[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 52 -57 .
[7] ZHANG Ying,LANG Yongmei,ZHAO Yuxiao,ZHANG Jianda,QIAO Peng,LI Shanping . Research on technique of aerobic granular sludge cultivationby seeding EGSB anaerobic granular sludge[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(4): 56 -59 .
[8] Yue Khing Toh1， XIAO Wendong2， XIE Lihua1. Wireless sensor network for distributed target tracking: practices via real test bed development[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 50 -56 .
[9] SUN Weiwei， WANG Yuzhen. Finite gain stabilization of singlemachine infinite bus system subject to saturation[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 69 -76 .
[10] SUN Yu-li,LI De-fa,ZUO Dun-wen,QI mei . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(6): 19 -23 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd