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Volume 27 Issue 3
Mar.  2005
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Wang Xiao-ye, Wang Zheng-ou. An Improved K-Nearest Neighbor Algorithm[J]. Journal of Electronics & Information Technology, 2005, 27(3): 487-491.
Citation: Wang Xiao-ye, Wang Zheng-ou. An Improved K-Nearest Neighbor Algorithm[J]. Journal of Electronics & Information Technology, 2005, 27(3): 487-491.

An Improved K-Nearest Neighbor Algorithm

  • Received Date: 2003-11-13
  • Rev Recd Date: 2004-04-26
  • Publish Date: 2005-03-19
  • This paper presents a improved K-NN algorithm. The CURE clustering is carried out to select the subset of the training set. It can reduce the volume of the training set and omit the outlier. Therefore it can lead both to computational efficiency and to higher classification accuracy. In the algorithm, the weights of each feature are learned using neural network. The feature weights are used in the nearest measure computation such that the important features contribute more in the nearest measure. Experiments on several UCI databases and practical data sets show the efficiency of the algorithm.
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  • Shin C, Yun U, Kim H, Park S. A hybrid approach of neural network and memory-based learning to data mining[J].IEEE Trans. on Neural Networks.2000, 11(3):637-[2]Wettschereck D, Aha D W, Mohri T. A review and empirical evaluation of feature weighting metbords for a class of lazy learning algorithms. AI Review, 1997, 11 (2): 273 - 314.[3]范明,孟小峰.数据挖掘概念与技术,北京:机械工业出版社,2001,第七章第七节.[4]Kuncheva L I. Fitness Functions in Editing k-nn Reference Set by Genetic Algorithms[J].Pattern Recognition.1997, 30(6):1041-[5]Setiono R, Liu H. Neural-network feature selector. IEEE Trans.on Neural Networks, 1997 8(3): 654 - 662.[6]Guha S, Rastugi R, Shim K. CURE: An efficient clustering algorithm for large databases. In Proc. 1998 ACM-SIGMOD Int.Conf. Management of Data (SIGMOD98), Seattle, WA, June 1998:73 - 84.[7]Pemg C, Wang H, Zhang S, parker D. Landmarks: A new model for similarity-based pattern querying in time series databases.IEEE Conf. on Data Engineering, 2000:33 - 44.[8]Quinlan J R. C4.5: Programs for Machine Learning. San Mateo,CA: Morgan Kaufmann, 1993, Chapter 3.
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