Back to Search Start Over

A Comparative Study on TIBA Imputation Methods in FCMdd-Based Linear Clustering with Relational Data.

Authors :
Yamamoto, Takeshi
Honda, Katsuhiro
Notsu, Akira
Ichihashi, Hidetomo
Source :
Advances in Fuzzy Systems; 2011, p1-10, 10p
Publication Year :
2011

Abstract

Relational fuzzy clustering has been developed for extracting intrinsic cluster structures of relational data and was extended to a linear fuzzy clustering model based on Fuzzy c-Medoids (FCMdd) concept, in which Fuzzy c-Means-(FCM-) like iterative algorithm was performed by defining linear cluster prototypes using two representative medoids for each line prototype. In this paper, the FCMdd-type linear clustering model is further modified in order to handle incomplete data including missing values, and the applicability of several imputation methods is compared. In several numerical experiments, it is demonstrated that some pre-imputation strategies contribute to properly selecting representative medoids of each cluster. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
16877101
Database :
Complementary Index
Journal :
Advances in Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
70694774
Full Text :
https://doi.org/10.1155/2011/265170