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第5期 黄琴,等:代价敏感数据的多标记特征选择算法 ·937· [3]郑伟,王朝坤,刘璋,等.一种基于随机游走模型的多标 特征选择算法).模式识别与人工智能,2016,29(3): 签分类算法.计算机学报,2010,33(8):1418-1426. 240-251. ZHENG Wei,WANG Chaokun,LIU Zhang,et al.A multi- LIU Jinghua,LIN Menglei,WANG Chenxi,et al.Multi- label classification algorithm based on random walk mod- label feature selection algorithm based on local el[J].Chinese journal of computers,2010,33(8): subspace[J].Pattern recognition and artificial intelligence. 1418-1426. 2016,29(3:240-251. [4]李宇峰,黄圣君,周志华.一种基于正则化的半监督多标 [15]LEE J,LIM H,KIM D W.Approximating mutual inform- 记学习方法[J】.计算机研究与发展,2012,49(6): ation for multi-label feature selection[J].Electronics let- 1272-1278 ters,2012,48(15):929-930. 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Rough set approach to multi￾attribute decision analysis[J]. European journal of opera￾tional research, 1994, 72(3): 443–459. [6] 刘清. Rough 集及 Rough 推理 [M]. 北京: 科学出版社, 2001. [7] SUN Liang, JI Shuiwang, YE Jieping. Multi-label dimen￾sionality reduction[M]. Florida: CRC Press, 2013: 20–22. [8] ZHANG Yin, ZHOU Zhihua. Multi-label dimensionality reduction via dependence maximization[C]//Proceedings of the 23rd National Conference on Artificial Intelligence. Chicago, Illinois, 2008: 1503−1505. [9] YU Kai, YU Shipeng, TRESP V. Multi-label informed latent semantic indexing[C]//Proceedings of the 28th An￾nual International ACM SIGIR Conference on Research and Development in Information Retrieval. Salvador, Brazil, 2005: 258−265. [10] 段洁, 胡清华, 张灵均, 等. 基于邻域粗糙集的多标记分 类特征选择算法 [J]. 计算机研究与发展, 2015, 52(1): 56–65. DUAN Jie, HU Qinghua, ZHANG Lingjun, et al. Feature selection for multi-label classification based on neighbor￾hood rough sets[J]. 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ZHANG Zhenhai, LI Shining, LI Zhigang, et al. Multi-la￾bel feature selection algorithm based on information en￾tropy[J]. Journal of computer research and development, 2013, 50(6): 1177–1184. [16] YANG Qiang, WU Xindong. 10 challenging problems in data mining research[J]. International journal of informa￾tion technology & decision making, 2006, 5(4): 597–604. [17] 徐章艳 , 刘作鹏 , 杨炳儒 , 等 . 一个复杂度 为 max(O(|C||U|),O(|C| 2 |U/C|)) 的快速属性约简算法 [J]. 计 算机学报, 2006, 29(3): 391–399. XU Zhangyan, LIU Zuopeng, YANG Bingru, et al. A quick attribute reduction algorithm with complexity of max(O(|C||U|),O(|C| 2 |U/C|))[J]. Chinese journal of com￾puters, 2006, 29(3): 391–399. [18] WU Binglong, QIAN Wenbin, HUANG Qin, et al. Cost￾Sensitive multi-label feature selection algorithm based on positive approximation[C]//Fuzzy Systems and Data Min￾ing IV-Proceedings of FSDM 2018. Bangkok, Thailand, 2018: 381−386. [19] QIAN Yuhua, LIANG Jiye, PEDRYCZ W, et al. Positive approximation: an accelerator for attribute reduction in rough set theory[J]. Artificial intelligence, 2010, 174(9/10): 597–618. [20] WEI Wei, WU Xiaoying, LIANG Jiye, et al. Discernibil￾ity matrix based incremental attribute reduction for dy￾namic data[J]. Knowledge-based systems, 2018, 140: 142–157. [21] ELISSEEFF A, WESTON J. A kernel method for multi￾labelled classification[C]//Proceedings of the 14th Inter￾national Conference on Neural Information Processing Systems: Natural and Synthetic. Vancouver, Canada, 2001: 681−687. [22] TROHIDIS K, TSOUMAKAS G, KALLIRIS G, et al. Multi-label classification of music into emotions[C]//Pro￾ceedings of the 9th International Society for Music In￾formation Retrieval Conference. Philadelphia, PA, 2008: 325−330. [23] 第 5 期 黄琴,等:代价敏感数据的多标记特征选择算法 ·937·
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