第2期 郭龙伟，等：基于测度学习支持向量机的钢琴乐谱难度等级识别 ·201· of university of electronic science and technology of China, [19]HOSMER D W,LEMESHOW S.Applied logistic regres- 2011,40(1):2-10 sion[M].New York:Wiley,2000:31-46. [9]LI Shutao,KWOK J T,ZHU Hailong,et al.Texture clas-si- [20]WESTON J,WATKINS C.Multi-class support vector ma- fication using the support vector machines[J].Pattern recog- chines,CSD-TR-98-04[R/OL].Egham:Royal Holloway nition,2003.36(12):2883-2893. University of London,1998:1-10. [10]SIMON T,KOLLER D.Support vector machine active [21]CHANG C C,LIN C J.LIBSVM-a library for support learning with applications to text classification[J].The vector machines[J/OL].ACM transactions on intelligent journal of machine learning research,2002,2:45-66. systems and technology,2011,2(3):27. [11]OSUNA E,FREUND R,GIROSIT F.Training support [22]徐晓明.SVM参数寻优及其在分类中的应用[D].大连： vector machines:an application to face detection[Cl//IEEE 大连海事大学，2014：6-58. Computer Society Conference on Computer Vision and XU Xiaoming.SVM parameter optimization and its applic- Pattern Recognition.San Juan,Puerto Rico,USA:IEEE, ation in the classification[D].Dalian:Dalian Maritime Uni- 1997:130-136. versity,2014:6-58. [12]WAN V,CAMPBELL W M.Support vector machines for 作者简介： speaker verification and identification[C]//Neural Net- 郭龙伟，男，1990年生，硕士研究 works for Signal Processing X.Proceedings of the 2000 生，主要研究方向为音乐信息检索。 IEEE Signal Processing Society Workshop.Sydney,NSW, Australia:IEEE,2000,2:775-784. [13]SCHOLKOPF B,SMOLA,A J.Learning with kernels[M]. GMD-For Schungszentrum Information Stechnik,1998: 5-93. [14]KULIS B.Metric learning:a survey[J].Foundations and 关欣，女，1977年生，研究员，主 trends in machine learning,2012,5(4):287-364. 要研究方向为音乐信息检索、统计学 [15]WEINBERGER K Q,SAUL L K.Distance metric learn- 习、凸优化理论和音乐信号处理。 ing for large margin nearest neighbor classification[J]. Journal of machine learning research,2009,10:207-244. [16]HSU C W,LIN C J.A comparison of methods for multi- class support vector machines[J].IEEE transactions on neural networks,2002,13(2):415-425. 李锵，男，1974年生，教授，博士 生导师，主要研究方向为医学图像处 [17]MIDI Manufacturers Association.An introduction to 理、智能信息处理、滤波器设计、数字 MIDI[M].California:MIDI Manufacturers Association, 系统和微系统设计。发表学术论文 2009:1-16. 30余篇，出版专著和教材8部。 [18]Fours set data sources[EB/OL].[2015-07-24].http://www. 8notes.com.of university of electronic science and technology of China, 2011, 40(1): 2–10. LI Shutao, KWOK J T, ZHU Hailong, et al. Texture clas-si￾fication using the support vector machines[J]. Pattern recog￾nition, 2003, 36(12): 2883–2893. [9] SIMON T, KOLLER D. Support vector machine active learning with applications to text classification[J]. The journal of machine learning research, 2002, 2: 45–66. [10] OSUNA E, FREUND R, GIROSIT F. Training support vector machines: an application to face detection[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Juan, Puerto Rico, USA: IEEE, 1997: 130–136. [11] WAN V, CAMPBELL W M. Support vector machines for speaker verification and identification[C]//Neural Net￾works for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop. Sydney, NSW, Australia: IEEE, 2000, 2: 775–784. [12] SCHÖLKOPF B, SMOLA, A J. Learning with kernels[M]. GMD-For Schungszentrum Information Stechnik, 1998: 5–93. [13] KULIS B. Metric learning: a survey[J]. Foundations and trends in machine learning, 2012, 5(4): 287–364. [14] WEINBERGER K Q, SAUL L K. Distance metric learn￾ing for large margin nearest neighbor classification[J]. Journal of machine learning research, 2009, 10: 207–244. [15] HSU C W, LIN C J. A comparison of methods for multi￾class support vector machines[J]. IEEE transactions on neural networks, 2002, 13(2): 415–425. [16] MIDI Manufacturers Association. An introduction to MIDI[M]. California: MIDI Manufacturers Association, 2009: 1–16. [17] Fours set data sources[EB/OL]. [2015-07-24]. http://www. 8notes.com. [18] HOSMER D W, LEMESHOW S. Applied logistic regres￾sion[M]. New York: Wiley, 2000: 31–46. [19] WESTON J, WATKINS C. Multi-class support vector ma￾chines, CSD-TR-98-04[R/OL]. Egham: Royal Holloway University of London, 1998: 1–10. [20] CHANG C C, LIN C J. LIBSVM——a library for support vector machines[J/OL]. ACM transactions on intelligent systems and technology, 2011, 2(3): 27. [21] 徐晓明. SVM 参数寻优及其在分类中的应用[D]. 大连: 大连海事大学, 2014: 6–58. XU Xiaoming. SVM parameter optimization and its applic￾ation in the classification[D]. Dalian: Dalian Maritime Uni￾versity, 2014: 6–58. [22] 作者简介： 郭龙伟，男，1990 年生，硕士研究 生，主要研究方向为音乐信息检索。 关欣，女，1977 年生，研究员，主 要研究方向为音乐信息检索、统计学 习、凸优化理论和音乐信号处理。 李锵，男，1974 年生，教授，博士 生导师，主要研究方向为医学图像处 理、智能信息处理、滤波器设计、数字 系统和微系统设计。发表学术论文 30 余篇，出版专著和教材 8 部。 第 2 期 郭龙伟，等：基于测度学习支持向量机的钢琴乐谱难度等级识别 ·201·