Fuzzy Soft Set Clustering for Categorical Data
Categorical data clustering is difficult because categorical data lacks natural order and can comprise groups of data only related to specific dimensions. Conventional clustering, such as k-means, cannot be openly used to categorical data. Numerous categorical data using clustering algorithms, for...
Saved in:
Main Authors: | Iwan Tri Riyadi, Yanto, Ani, Apriani, Rofiul, Wahyudi, Cheah, Wai Shiang, Suprihatin, in, Rahmat, Hidayat |
---|---|
Format: | Article |
Language: | English |
Published: |
Society of Visual Informatics, and Institute of Visual Informatics - UKM and Soft Computing and Data Mining Centre - UTHM
2024
|
Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/47246/1/2364-6612-1-PB.pdf http://ir.unimas.my/id/eprint/47246/ https://joiv.org/index.php/joiv/article/view/2364 http://dx.doi.org/10.62527/joiv.8.1.2364 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rough clustering for web transactions
by: Yanto, Iwan Tri Riyadi
Published: (2011) -
Soft set theory based decision support system for mining electronic government dataset
by: Witarsyah, Deden, et al.
Published: (2020) -
Empirical analysis of rough set categorical clustering techniques based on rough purity and value set
by: Uddin, Jamal
Published: (2017) -
Depression Detection on Mandarin Text through Bert Model
by: Yung, Teck Kiong, et al.
Published: (2024) -
Rough set approach for categorical data clustering
by: Herawan, Tutut
Published: (2010)