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Volume 37 Issue 7
Jul.  2015
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Zhi Wei-mei, Zhang Ting, Fan Ming. k-nearest Neighbor Classification Based on Influence Function[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1626-1632. doi: 10.11999/JEIT141433
Citation: Zhi Wei-mei, Zhang Ting, Fan Ming. k-nearest Neighbor Classification Based on Influence Function[J]. Journal of Electronics & Information Technology, 2015, 37(7): 1626-1632. doi: 10.11999/JEIT141433

k-nearest Neighbor Classification Based on Influence Function

doi: 10.11999/JEIT141433
  • Received Date: 2014-11-13
  • Rev Recd Date: 2015-04-03
  • Publish Date: 2015-07-19
  • Classification is a supervised learning. It determines the class label of an unlabeled instance by learning model based on the training dataset. Unlike traditional classification, this paper views classification problem from another perspective, that is influential function. That is, the class label of an unlabeled instance is determined by the influence of the training data set. Firstly, the idea of classification is introduced based on influence function. Secondly, the definition of influence function is given and three influence functions are designed. Finally, this paper proposes k-nearest neighbor classification method based on these three influence functions and applies it to the classification of imbalanced data sets. The experimental results on 18 UCI data sets show that the proposed method improves effectively the k-nearest neighbor generalization ability. Besides, the proposed method is effective for imbalanced classification.
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