Combination Entropy and Combination Granulation in Incomplete Information System

2006 ◽  
pp. 184-190 ◽  
Author(s):  
Yuhua Qian ◽  
Jiye Liang
Keyword(s):  
Information System ◽  
Incomplete Information ◽  
Incomplete Information System

Missing Data Clustering Based on Incomplete Information System

2014 ◽  
Vol 687-691 ◽  
pp. 1500-1503
Author(s):  
Yong Lin Leng
Keyword(s):  
Information System ◽  
Missing Data ◽  
Incomplete Information ◽  
Data Clustering ◽  
Clustering Methods ◽  
Data Set ◽  
Incomplete Information System ◽  
Data Measurement ◽  
Cluster Data ◽  
Test Algorithm

With the development of information technology and data collection capabilities improve, the amount of data accumulated increase, missing data problems are more and more obvious. Traditional clustering methods can not cluster data set which contained missing data directly. In this paper, we proposed a novel missing data measurement method based on the incomplete information system theory and designed the similarity measure criterion for the discrete and successive of attributes separately. The experiment uses K-means clustering to test algorithm accuracy from different missing data rate and different amount of data two aspects, results demonstrate that the method can cluster missing data set efficiently and accurately.

Sign in / Sign up

Export Citation Format

Share Document