[1] |
COVER T, HART P. Nearest neighbor pattern classification[J]. IEEE Transactions on Information Theory, 2002, 13(1): 21-27.
|
[2] |
XU B H, FU Y W, JIANG Y G, et al. Heterogeneous knowledge transfer in video emotion recognition, attribution and summarization[J]. IEEE Transactions on Affective Computing, 2018, 9(2): 255-270.
|
[3] |
周志华. 机器学习[M]. 北京: 清华大学出版社, 2016.
|
[4] |
张敏灵. 一种新型多标记懒惰学习算法[J]. 计算机研究与发展, 2012, 49(11): 2271-2282.
|
[5] |
FRIEDMAN J, HASTIE T, TIBSHIRANI R. The Elements of Statistical Learning[M]. Berlin: Springer, 2001.
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[6] |
WU X, KUMAR V, QUINLAN J R, et al. Top 10 algorithms in data mining[J]. Knowledge and Information Systems, 2008, 14(1): 1-37.
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[7] |
KONONENKO I, KUKAR M. Machine Learning and Data Mining: Introduction to Principles and Algorithms[M]. Chichester: Harwood Publishing Limited, 2007.
|
[8] |
LI Y, MAGUIRE L. Selecting critical patterns based on local geometrical and statistical information[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(6): 1189-1201.
|
[9] |
MUJA M, LOWE D G. Scalable nearest neighbor algorithms for high dimensional data[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(11): 2227-2240.
|
[10] |
MARCHIORI E. Class conditional nearest neighbor for large margin instance selection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(2): 364-370.
|
[11] |
ANGIULLI F. Fast nearest neighbor condensation for large data sets classification[J]. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(11): 1450-1464.
|
[12] |
LIU T, MOORE A W, YANG K, et al. An investigation of practical approximate nearest neighbor algorithms[C]// Proc of Conference on Neural Information Processing Systems. Vancouver, Canada: MIT Press, 2005: 825-832.
|
[13] |
MCFEE B, LANCKRIET G R G. Large-scale music similarity search with spatial trees[C]// Proceedings of the 12th International Society for Music Information Retrieval Conference. Florida: ISMIR Press, 2014: 566-574.
|
[14] |
GARCIA S, DERRAC J, CANO J, et al. Prototype selection for nearest neighbor classification: Taxonomy and empirical study[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(3): 417-435.
|
[15] |
HSIEH C J, SI S, DHILLON I S. A divide-and-conquer solver for kernel support vector machines[C]// Proceedings of the 27th International Conference on Machine Learning. Haifa: IMLS Press, 2014: 566-574.
|
[16] |
FRIEDMAN J H, BENTLEY J L, FINKEL R A. An algorithm for finding best matches in logarithmic expected time[J]. ACM Transactions on Mathematical Software, 1977, 3(3): 209-226.
|
[17] |
VERMA N, KPOTUFE S, DASGUPTA S. Which spatial partition trees are adaptive to intrinsic dimension?[C]// Proceedings of the 25h Conference on Uncertainty in Artificial Intelligence. Montreal, Canada: AUAI Press, 2009: 565-574.
|
[18] |
SLANEY M, CASEY M. Locality-sensitive hashing for finding nearest neighbors [J]. IEEE Signal Processing Magazine, 2008, 25(2): 128-131.
|
[19] |
OLVERA-LPEZ J A, CARRASCO-OCHOA J A, MARTNEZ-TRINIDAD J F, et al. A review of instance selection methods[J]. Artificial Intelligence Review, 2010, 34(2): 133-143.
|
[20] |
BRIGHTON H, MELLISH C. Advances in instance selection for instance-based learning algorithms[J]. Data Mining and Knowledge Discovery, 2002, 6(2): 153-172.
|
[21] |
HART P. The condensed nearest neighbor rule[J]. IEEE Transactions on Information Theory, 1968, 14(3): 515-516.
|
[22] |
ANGIULLI F, FOLINO G. Distributed nearest neighbor-based condensation of very large data sets[J]. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(12): 1593-1606.
|
[23] |
NIKOLAIDIS K, GOULERMAS J Y, WU Q H. A class boundary preserving algorithm for data condensation[J]. Pattern Recognition, 2011, 44(3): 704-715.
|
[24] |
ZHANG H, SUN G. Optimal reference subset selection for nearest neighbor classification by tabu search[J]. Pattern Recognition, 2002, 35(7): 1481-1490.
|
[25] |
王熙照, 王亚东, 湛燕, 等. 学习特征权值对 K-均值聚类算法的优化[J]. 计算机研究与发展, 2003, 40(6): 869-873.
|
[26] |
杨润玲, 高新波. 基于加权模糊c均值聚类的快速图像自动分割算法[J]. 中国图象图形学报, 2007, 12(12): 2105-2112.
|
[27] |
DEMAR J. Statistical comparisons of classifiers over multiple data sets[J]. Journal of Machine Learning Research, 2006, 7(1): 1-30.
|
[28] |
CHANG C C, LIN C J. LIBSVM: A library for support vector machines[J]. ACM Transactions on Intelligent Systems and Technology, 2011, 2(3): No.27.
|
[29] |
BLAKE C L, MERZ C J. UCI Repository of machine learning databases[EB/OL]. [2017-06-15] http://www. ics. uci. edu/~ mlearn/MLRepository. Html, 1998.
|
[30] |
WILCOXON F. Individual comparisons by ranking methods[J]. Biometrics Bulletin, 1945, 1(6): 80-83.
|
[31] |
GARCA-OSORIO C, HARO-GARCA A, GARCA-PEDRAJAS N. Democratic instance selection: A linear complexity instance selection algorithm based on classifier ensemble concepts[J]. Artificial Intelligence, 2010, 174(5): 410-441.
|
[32] |
KORDOS M, BLACHNIK M, STRZEMPA D. Do we need whatever more than k-NN?[C]// Proceedings of the 10th International Conference on Artificial Intelligence and Soft Computing. Zakopane, Poland: Springer, 2010: 414-421.
|
[1] |
COVER T, HART P. Nearest neighbor pattern classification[J]. IEEE Transactions on Information Theory, 2002, 13(1): 21-27.
|
[2] |
XU B H, FU Y W, JIANG Y G, et al. Heterogeneous knowledge transfer in video emotion recognition, attribution and summarization[J]. IEEE Transactions on Affective Computing, 2018, 9(2): 255-270.
|
[3] |
周志华. 机器学习[M]. 北京: 清华大学出版社, 2016.
|
[4] |
张敏灵. 一种新型多标记懒惰学习算法[J]. 计算机研究与发展, 2012, 49(11): 2271-2282.
|
[5] |
FRIEDMAN J, HASTIE T, TIBSHIRANI R. The Elements of Statistical Learning[M]. Berlin: Springer, 2001.
|
[6] |
WU X, KUMAR V, QUINLAN J R, et al. Top 10 algorithms in data mining[J]. Knowledge and Information Systems, 2008, 14(1): 1-37.
|
[7] |
KONONENKO I, KUKAR M. Machine Learning and Data Mining: Introduction to Principles and Algorithms[M]. Chichester: Harwood Publishing Limited, 2007.
|
[8] |
LI Y, MAGUIRE L. Selecting critical patterns based on local geometrical and statistical information[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(6): 1189-1201.
|
[9] |
MUJA M, LOWE D G. Scalable nearest neighbor algorithms for high dimensional data[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014, 36(11): 2227-2240.
|
[10] |
MARCHIORI E. Class conditional nearest neighbor for large margin instance selection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(2): 364-370.
|
[11] |
ANGIULLI F. Fast nearest neighbor condensation for large data sets classification[J]. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(11): 1450-1464.
|
[12] |
LIU T, MOORE A W, YANG K, et al. An investigation of practical approximate nearest neighbor algorithms[C]// Proc of Conference on Neural Information Processing Systems. Vancouver, Canada: MIT Press, 2005: 825-832.
|
[13] |
MCFEE B, LANCKRIET G R G. Large-scale music similarity search with spatial trees[C]// Proceedings of the 12th International Society for Music Information Retrieval Conference. Florida: ISMIR Press, 2014: 566-574.
|
[14] |
GARCIA S, DERRAC J, CANO J, et al. Prototype selection for nearest neighbor classification: Taxonomy and empirical study[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(3): 417-435.
|
[15] |
HSIEH C J, SI S, DHILLON I S. A divide-and-conquer solver for kernel support vector machines[C]// Proceedings of the 27th International Conference on Machine Learning. Haifa: IMLS Press, 2014: 566-574.
|
[16] |
FRIEDMAN J H, BENTLEY J L, FINKEL R A. An algorithm for finding best matches in logarithmic expected time[J]. ACM Transactions on Mathematical Software, 1977, 3(3): 209-226.
|
[17] |
VERMA N, KPOTUFE S, DASGUPTA S. Which spatial partition trees are adaptive to intrinsic dimension?[C]// Proceedings of the 25h Conference on Uncertainty in Artificial Intelligence. Montreal, Canada: AUAI Press, 2009: 565-574.
|
[18] |
SLANEY M, CASEY M. Locality-sensitive hashing for finding nearest neighbors [J]. IEEE Signal Processing Magazine, 2008, 25(2): 128-131.
|
[19] |
OLVERA-LPEZ J A, CARRASCO-OCHOA J A, MARTNEZ-TRINIDAD J F, et al. A review of instance selection methods[J]. Artificial Intelligence Review, 2010, 34(2): 133-143.
|
[20] |
BRIGHTON H, MELLISH C. Advances in instance selection for instance-based learning algorithms[J]. Data Mining and Knowledge Discovery, 2002, 6(2): 153-172.
|
[21] |
HART P. The condensed nearest neighbor rule[J]. IEEE Transactions on Information Theory, 1968, 14(3): 515-516.
|
[22] |
ANGIULLI F, FOLINO G. Distributed nearest neighbor-based condensation of very large data sets[J]. IEEE Transactions on Knowledge and Data Engineering, 2007, 19(12): 1593-1606.
|
[23] |
NIKOLAIDIS K, GOULERMAS J Y, WU Q H. A class boundary preserving algorithm for data condensation[J]. Pattern Recognition, 2011, 44(3): 704-715.
|
[24] |
ZHANG H, SUN G. Optimal reference subset selection for nearest neighbor classification by tabu search[J]. Pattern Recognition, 2002, 35(7): 1481-1490.
|
[25] |
王熙照, 王亚东, 湛燕, 等. 学习特征权值对 K-均值聚类算法的优化[J]. 计算机研究与发展, 2003, 40(6): 869-873.
|
[26] |
杨润玲, 高新波. 基于加权模糊c均值聚类的快速图像自动分割算法[J]. 中国图象图形学报, 2007, 12(12): 2105-2112.
|
[27] |
DEMAR J. Statistical comparisons of classifiers over multiple data sets[J]. Journal of Machine Learning Research, 2006, 7(1): 1-30.
|
[28] |
CHANG C C, LIN C J. LIBSVM: A library for support vector machines[J]. ACM Transactions on Intelligent Systems and Technology, 2011, 2(3): No.27.
|
[29] |
BLAKE C L, MERZ C J. UCI Repository of machine learning databases[EB/OL]. [2017-06-15] http://www. ics. uci. edu/~ mlearn/MLRepository. Html, 1998.
|
[30] |
WILCOXON F. Individual comparisons by ranking methods[J]. Biometrics Bulletin, 1945, 1(6): 80-83.
|
[31] |
GARCA-OSORIO C, HARO-GARCA A, GARCA-PEDRAJAS N. Democratic instance selection: A linear complexity instance selection algorithm based on classifier ensemble concepts[J]. Artificial Intelligence, 2010, 174(5): 410-441.
|
[32] |
KORDOS M, BLACHNIK M, STRZEMPA D. Do we need whatever more than k-NN?[C]// Proceedings of the 10th International Conference on Artificial Intelligence and Soft Computing. Zakopane, Poland: Springer, 2010: 414-421.
|