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基于影響函數(shù)的k-近鄰分類

職為梅 張婷 范明

職為梅, 張婷, 范明. 基于影響函數(shù)的k-近鄰分類[J]. 電子與信息學(xué)報, 2015, 37(7): 1626-1632. doi: 10.11999/JEIT141433
引用本文: 職為梅, 張婷, 范明. 基于影響函數(shù)的k-近鄰分類[J]. 電子與信息學(xué)報, 2015, 37(7): 1626-1632. doi: 10.11999/JEIT141433
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

基于影響函數(shù)的k-近鄰分類

doi: 10.11999/JEIT141433
基金項目: 

國家自然科學(xué)基金(61170223)和河南省教育廳科學(xué)技術(shù)研究重點項目(14A520016)資助課題

k-nearest Neighbor Classification Based on Influence Function

  • 摘要: 分類是一種監(jiān)督學(xué)習(xí)方法,通過在訓(xùn)練數(shù)據(jù)集學(xué)習(xí)模型判定未知樣本的類標(biāo)號。與傳統(tǒng)的分類思想不同,該文從影響函數(shù)的角度理解分類,即從訓(xùn)練樣本集對未知樣本的影響來判定未知樣本的類標(biāo)號。首先介紹基于影響函數(shù)分類的思想;其次給出影響函數(shù)的定義,設(shè)計3種影響函數(shù);最后基于這3種影響函數(shù),提出基于影響函數(shù)的k-近鄰(kNN)分類方法。并將該方法應(yīng)用到非平衡數(shù)據(jù)集分類中。在18個UCI數(shù)據(jù)集上的實驗結(jié)果表明,基于影響函數(shù)的k-近鄰分類方法的分類性能好于傳統(tǒng)的k-近鄰分類方法,且對非平衡數(shù)據(jù)集分類有效。
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出版歷程
  • 收稿日期:  2014-11-13
  • 修回日期:  2015-04-03
  • 刊出日期:  2015-07-19

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