FUZZY CLUSTERING WITH WEIGHTING OF DATA VARIABLES
2000 ◽
Vol 08
(06)
◽
pp. 735-746
◽
Keyword(s):
We introduce an objective function-based fuzzy clustering technique that assigns one influence parameter to each single data variable for each cluster. Our method is not only suited to detect structures or groups of data that are not uniformly distributed over the structure's single domains, but gives also information about the influence of individual variables on the detected groups. In addition, our approach can be seen as a generalization of the well-known fuzzy c-means clustering algorithm.
2018 ◽
Vol 7
(5)
◽
pp. 164
◽
1994 ◽
Vol 02
(03)
◽
pp. 343-350
◽
2014 ◽
Vol 989-994
◽
pp. 1489-1492
◽
2017 ◽
Vol 7
(6)
◽
pp. 668-670
2020 ◽
Vol 15
◽
pp. 155892502097832