TY - JOUR
T1 - Density-Weighted Fuzzy C-Means Clustering
AU - Hathaway, Ritchard J.
AU - Hu, Yingkang
PY - 2009/1/1
Y1 - 2009/1/1
N2 - In this short paper, a unified framework for performing density-weighted fuzzy c-means (FCM) clustering of feature and relational datasets is presented. The proposed approach consists of reducing the original dataset to a smaller one, assigning each selected datum a weight reflecting the number of nearby data, clustering the weighted reduced dataset using a weighted version of the feature or relational data FCM algorithm, and if desired, extending the reduced data results back to the original dataset. Several methods are given for each of the tasks of data subset selection, weight assignment, and extension of the weighted clustering results. The newly proposed weighted version of the non-Euclidean relational FCM algorithm is proved to produce the identical results as its feature data analog for a certain type of relational data. Artificial and real data examples are used to demonstrate and contrast various instances of this general approach.
AB - In this short paper, a unified framework for performing density-weighted fuzzy c-means (FCM) clustering of feature and relational datasets is presented. The proposed approach consists of reducing the original dataset to a smaller one, assigning each selected datum a weight reflecting the number of nearby data, clustering the weighted reduced dataset using a weighted version of the feature or relational data FCM algorithm, and if desired, extending the reduced data results back to the original dataset. Several methods are given for each of the tasks of data subset selection, weight assignment, and extension of the weighted clustering results. The newly proposed weighted version of the non-Euclidean relational FCM algorithm is proved to produce the identical results as its feature data analog for a certain type of relational data. Artificial and real data examples are used to demonstrate and contrast various instances of this general approach.
KW - Clustering
KW - Data reduction
KW - Feature data
KW - fuzzy $c$-means (FCM) relational data
UR - https://digitalcommons.georgiasouthern.edu/math-sci-facpubs/27
UR - http://dx.doi.org/10.1109/TFUZZ.2008.2009458
U2 - 10.1109/TFUZZ.2008.2009458
DO - 10.1109/TFUZZ.2008.2009458
M3 - Article
SN - 1063-6706
VL - 19
JO - IEEE Transactions on Fuzzy Systems
JF - IEEE Transactions on Fuzzy Systems
ER -