Journal of Guangxi Normal University(Natural Science Edition) ›› 2010, Vol. 28 ›› Issue (1): 72-76.

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QENNI:A New Imputation Method for Missing Data

ZHANG Shi-chao, ZHU Man-long, HUANG Liang-chang   

  1. College of Computer Science and Information Technology,GuangxiNormal University,Guilin Guangxi 541004,China
  • Received:2009-12-04 Online:2010-03-20 Published:2023-02-07

Abstract: As the k-nearest neighbor imputation (kNNI)algorithm is often biased in choosing the k nearest neighbors of missing data,a new imputation method is put forward,Quadrant-Encapsidated-Nearest-Neighbor based Imputation method (QENNI),for missing values.The algorithm uses the quadrant nearest neighbors (points of the encapsulant) around a missing datum to impute the missing datum.It is not biased in selecting nearest neighbors.Experiments demonstrate that QENNI is much better than the kNNI method in imputed accuracy.

Key words: missing data, missing data imputation, kNNI method, QENNI method

CLC Number: 

  • TP181
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[1] SU Yi-juan, SUN Ke, DENG Zhen-yun, YIN Ke-jun. KNN Imputation Algorithm Based on LPP and l2,1 [J]. Journal of Guangxi Normal University(Natural Science Edition), 2015, 33(4): 55-62.
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