DocumentCode :
3660296
Title :
Weigted-KNN and its application on UCI
Author :
Zhang Li;Zhang Chengjin;Xu Qingyang;Liu Chunfa
Author_Institution :
School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, 264209, CHINA
fYear :
2015
Firstpage :
1748
Lastpage :
1750
Abstract :
K nearest neighbor classification algorithm (KNN) is one of relatively simple method in data mining classification techniques, study and research KNN classification algorithm for data classification and data mining technology has a very important significance. An attribute Weighted KNN(W-KNN) method is utilized for reducing the irrelevant attributes. And the weight parameter can distinguish the different effective of different attributes in classification. The weight of each attribute is determined by the method of sensitivity. Finally, The results reveal that Weighted KNN algorithm improves the correct classification performance in Wine data set.
Keywords :
"Classification algorithms","Training","Iris","Prediction algorithms","Glass","Data mining","Sensitivity"
Publisher :
ieee
Conference_Titel :
Information and Automation, 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICInfA.2015.7279570
Filename :
7279570
Link To Document :
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