Research Based on Euclid Distance with Weights of K——means Algorithm
[1]ZHANG Zhonglin,CAO Zhiyu,LI Yuantao.Research Based on Euclid Distance with Weights of K——means Algorithm[J].Journal of Zhengzhou University (Engineering Science),2010,31(01):92-.
Copy
Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
31卷
Number of periods:
2010 01
Page number:
92-
Column:
Public date:
2010-01-30
- Title:
- Research Based on Euclid Distance with Weights of K——means Algorithm
- Keywords:
- k_means algorithm; clustering; weight; coefficient of variation
- CLC:
- -
- DOI:
- -
- Abstract:
- Euclid distance is commonly used to measure distance in the traditional k_means algorithm．The k—means algorithm based on weighted Euclid distance is researched and presented to overcome the existing problems of similarity calculation in clustering analysis based on traditional Euclid distance when we have no anydomain knowledge about the data objects，the relative distance but not absolute distance is more accurately re—sponse to data distribution．Experiments on the standard database UCI show that the proposed method can produce ahigh accuracy clustering result．
- References:
- -
- Similar References:
Memo
-
Last Update:
1900-01-01