Computer Science ›› 2014, Vol. 41 ›› Issue (2): 166-169.
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LU Wei-sheng,GUO Gong-de,YAN Xuan-hui and CHEN Li-fei
| [1] 胡元,石冰.基于区域划分的kNN文本快速分类算法研究[J].计算机科学,2012,0:182-186 [2] Mitchell T M．Machine Learning[M].McGraw-Hill Companies Inc,1997:230-247 [3] Cover T M,Hart P E.Nearest Neighbor Pattern Classification[J]．IEEE Trans on Informati on Theory,1967,J3(1):21-27 [4] Wu X D,Kumar V,Quinlan J R,et al.Top 10algorithms indata mining[J]．Knowl Inf Syst,2008,14:1-37 [5] Dudani S A.The Distance-weighted kNearest Neighbor Rule[J]．IEEE Transactions on System,Man and Cybernetics,1976,SMC-6(4):325-327 [6] Liu H W,Zhang S C.Noisy data elimination using mutualk-nearest neighbor for classification mining[J].The Journalof Systems and Software,2012(85):1067-1074 [7] Bhatia N,Vandana.Survey of nearest neighbor techniques[J]．International Journal of Computer Science and Information Security,2008,8(2):302-305 [8] 张孝飞,黄河燕.一种采用聚类技术改进的 KNN 文本分类方法[J].模式识别与人工智能,2009,2(6):936-940 [9] 余鹰,苗夺谦,刘财辉,等．基于变精度粗糙集的KNN分类改进算法[J].模式识别与人工智能,2012,5(4):618-623 [10] Guo G D,Wang H,Bell D,et al.KNN Model-Based Approach in Classification[J].Proc of the OTM Confederated International Conference on CoopIS,DOA,and OD BASE.Catania,Italy,2003:986-996 [11] 陈黎飞,郭躬德．最近邻分类的多代表点学习算法[J]．模式识别与人工智能,2011,4(6):883-888 [12] Gou J P,Xiong T S,Kuang Y．A Novel Weighted Votingfor K-Nearest Neighbor Rule[J]．Journal of Computers,2011,6(5):833-840 [13] Ding C,He X F．K-nearest-neighbor consistency in data-clustering:incorporating local information into global optimization[C]∥Proceedings of ACM Symposium on Applied Computing (SAC)．2004:584-589 [14] Chidananda K,Krishna G．The condensed nearest neighbor or rule using the concept of mutual nearest neighbor[J].IEEE Trans on Information Theory,1979,IT-25:488-490 [15] 陈黎飞,郭躬德,姜青山.自适应的软子空间聚类算法[J].软件学报,2010,1(10):2513-2523 [16] Huang J Z,Ng M K,Rong H,et a1.Automated variable weighting in k-means type clustering[J].IEEE Trans on Pattern Analysis and Machine Intelligence,2005,7(5):657-668 [17] 张健飞,陈黎飞,郭躬德,等.多代表点子空间分类算法[J].计算机科学与探索,2011(11):1037-1048 [18] 李南,郭躬德．基于子空间集成的概念漂移数据流分类算法[J].计算机系统应用,2011,0(12):241-248 |
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