Journal of Shandong University(Engineering Science) ›› 2022, Vol. 52 ›› Issue (2): 80-88.doi: 10.6040/j.issn.1672-3961.0.2021.316

Previous Articles    

An online active learning algorithm for multi-label classification

GONG Kailun, ZHAI Tingting*, TANG Hongcheng   

  1. College of Information Engineering, Yangzhou University, Yangzhou 225127, Jiangsu, China
  • Published:2022-04-20

CLC Number: 

  • TP181
[1] ZHANG M L, ZHOU Z H. A review on multi-label learning algorithms[J]. IEEE Transactions on Knowledge and Data Engineering, 2014, 26(8):1819-1837.
[2] AL-SALEMI B, AYOB M, NOAH S. Feature ranking for enhancing boosting-based multi-label text categorization[J]. Expert Systems with Applications, 2018, 113:531-543.
[3] LIU Y, WEN K, GAO Q, et al. SVM based multi-label learning with missing labels for image annotation[J]. Pattern Recognition, 2018, 78:307-317.
[4] XU X S, JIANG Y, PENG L, et al. Ensemble approach based onconditional random field for multi-label image and video annotation[C] //Proceedings of the 19th International Conference on Multimedea 2011. Scottsdale, AZ, USA: ACM, 2011: 1377-1380.
[5] SUN L, ZU C, SHAO W, et al. Reliability-based robust multi-atlas label fusion for brain MRI segmentation[J]. ArtificialIntelligence in Medicine, 2019, 96:12-24.
[6] TSOUMAKAS G, KATAKIS I, VLAHAVAS I. Mining multi-label data[M] //Data mining and knowledge discovery handbook. Boston, USA: Springer, 2009: 667-685.
[7] BOUTELL M R, LUO J, SHEN X, et al. Learning multi-label scene classification[J]. Pattern Recognition, 2004, 37(9): 1757-1771.
[8] ZHANG M L, ZHOU ZH. ML-KNN: a lazy learning approach to multi-label learning[J]. Pattern Recognition, 2007, 40(7): 2038-2048.
[9] AGGARWA L, CHARU C. A survey of stream classification algorithms[J]. Data Classification: Algorithms and Applications, 2014: 245-274.
[10] KREMPL G, SPILIOPOULOU M, STEFANOWSKI J, et al. Open challenges for data stream mining research[J]. Acm Sigkdd Explorations Newsletter, 2014, 16(1):1-10.
[11] 翟婷婷,高阳,朱俊武.面向流数据分类的在线学习综述[J].软件学报,2020,31(4):912-931. ZHAI Tingting, GAO Yang, ZHU Junwu. Survey of online learning algorithms for streaming data classification[J]. Journal of Software, 2020, 31(4):912-931.
[12] ZHANG X, GRAEPEL T, HERBRICH R. Bayesianonline learning for multi-label and multi-variate performance measures[C] //Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, JMLR Workshop and Conference Proceedings.Sardinia, Italy: JMLR Workshop and Conference Proceedings, 2010: 956-963.
[13] HIGUCHI D, OZAWA S. Aneural network model for online multi-task multi-label pattern recognition[C] //International Conference on Artificial Neural Networks and Machine Learning. Berlin, Heidelberg:Springer, 2013: 162-169.
[14] PARK S, CHOI S. Online multi-label learning with acceleratednonsmooth stochastic gradient descent[C] //IEEE International Conference on Acoustics, Speech and Signal Processing. Vancouver, Canada: IEEE International Conference on Acoustics, 2013: 3322-3326.
[15] LUGHOFER, EDWIN. On-line active learning: a new paradigm to improve practical useability of data stream modeling methods[J]. Information Sciences, 2017, 415: 356-376.
[16] HUANG S J, LI G X, HUANG W Y, et al. Incremental multi-label learning with active queries[J]. Journal of Computer Science and Technology, 2020, 35(2):234-246.
[17] HUA X S, QI G J. Online multi-label active annotation: towards large-scale content-based video search[C] //Proceedings of the 16th ACM International Conference on Multimedia. New York, USA: Association for Computing Machinery, 2008: 141-150.
[18] 徐美香,孙福明,李豪杰.主动学习的多标签图像在线分类[J].中国图象图形学报,2015,20(2):237-244. XU Meixiang, SUN Fuming, LI Haojie. Online multi-label image classification with active learning[J]. Journal of Image and Graphics, 2015, 20(2): 237-244.
[19] CRAMMER K, SINGER Y. A family of additive online algorithms for category ranking[J]. Journal of Machine Learning Research, 2003, 3: 1025-1058.
[20] GUO X, ZHANG Y, XU J. Online multi-label passive aggressive active learning algorithm based on binary relevance[C] // International Conference on Neural Information Processing. Cham, Germany: Springer, 2017: 256-266.
[21] GIBAJA E L, VENTURA S. Atutorial on multi-label learning[J]. ACM Computing Surveys, 2015, 47(3):1-38.
[22] CRAMMER K, DEKEL O, KESHET J, et al. Online passive-aggressive algorithms[J]. Journal of Machine Learning Research, 2006, 7:551-585.
[23] DUCHI J C, SHALEV-SHWARTZ S, SINGER Y, et al. Composite objective mirror descent[J]. Learning/statistics & Optimisation Theory & Algorithms, 2010: 14-26.
[24] CRAMMER K, DREDZE M, PEREIRA F. Confidence-weighted linear classification for text categorization[J]. Journal of Machine Learning Research, 2012, 13: 1891-1926.
[25] LU J, ZHAO P, HOI S C H. Onlinepassive-aggressive active learning[J]. Machine Learning, 2016, 103(2): 141-183.
[1] Yan PENG,Tingting FENG,Jie WANG. An integrated learning approach for O3 mass concentration prediction model [J]. Journal of Shandong University(Engineering Science), 2020, 50(4): 1-7.
[2] Yibin WANG,Tianli LI,Yusheng CHENG,Kun QIAN. Label distribution learning based on kernel extreme learning machine auto-encoder [J]. Journal of Shandong University(Engineering Science), 2020, 50(3): 58-65.
[3] Chunyang LI,Nan LI,Tao FENG,Zhuhe WANG,Jingkai MA. Abnormal sound detection of washing machines based on deep learning [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 108-117.
[4] Yingda LI,Zongxia XIE. Support vector regression algorithm based on kernel similarity reduced strategy [J]. Journal of Shandong University(Engineering Science), 2019, 49(3): 8-14.
[5] Kuo PANG,Siqi CHEN,Xiaoying SONG,Li ZOU. Linguistic concept formal decision context analysis based on granular computing [J]. Journal of Shandong University(Engineering Science), 2018, 48(6): 74-81.
[6] WANG Tingting, ZHAI Junhai, ZHANG Mingyang, HAO Pu. K-NN algorithm for big data based on HBase and SimHash [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 54-59.
[7] HE Zhengyi, ZENG Xianhua, GUO Jiang. An ensemble method with convolutional neural network and deep belief network for gait recognition and simulation [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 88-95.
[8] CUI Xiaosong, WANG Ying, MENG Jia, ZOU Li. Online business self-evaluation system based on linguistic-valued similarity reasoning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(1): 1-7.
[9] YAO Yu, FENG Jian, ZHANG Huaguang, HAN Kezhen. Weighted hyper-ellipsoidal support vector data description with negative samples for outlier detection [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 195-202.
[10] LI Sushu, WANG Shitong, LI Tao. A feature selection method based on LS-SVM and fuzzy supplementary criterion [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(3): 34-42.
[11] LIU Yingxia, WANG Xichang, TANG Xiaoli, CHANG Faliang. Object detection algorithm based on Bayesian probability estimation in wavelet domain [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(2): 63-70.
[12] CHEN Zehua, SHANG Xiaohui, CHAI Jing. Neighborhood related multiple-instance classifiers based on integrated Hausdorff distance [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 15-22.
[13] WANG Zhiqiang, WEN Yimin, LI Fang. Collaborative recommendation for scenic spots based on multi-aspect ratings [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 54-61.
[14] HE Zhengyi, ZENG Xianhua, QU Shengwei, WU Zhilong. The time series prediction model based on integrated deep learning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 40-47.
[15] WANG Mei, ZENG Zhaohu, SUN Yingqi, YANG Erlong, SONG Kaoping. Bayesian combination of SVR on regularization path based on KNN of input [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 8-14.
Full text



No Suggested Reading articles found!