MKNN: Modified K-Nearest Neighbor

被引：0

作者：

Parvin, Hamid ^{[1
]}

Alizadeh, Hoscin ^{[1
]}

Minael-Bidgoli, Behrouz ^{[1
]}

机构：

[1] Iran Univ Sci & Technol, Dept Comp Engn, Tehran, Iran

来源：

WCECS 2008: WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE | 2008年

关键词：

MKNN; KNN Classification; Modified K-Nearest Neighbor; Weighted K-Nearest Neighbor;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, a new classification method for enhancing the performance of K-Nearest Neighbor is proposed which uses robust neighbors in training data. This new classification method is called Modified K-Nearest Neighbor, MKNN. Inspired the traditional KNN algorithm, the main idea is classifying the test samples according to their neighbor tags. This method is a kind of weighted KNN so that these weights are determined using a different procedure. The procedure computes the fraction of the same labeled neighbors to the total number of neighbors. The proposed method is evaluated on five different data sets. Experiments show the excellent improvement in accuracy in comparison with KNN method.

引用

页码：831 / 834

页数：4

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