A Novel Semi-Supervised Fuzzy C-Means Clustering Algorithm Using Multiple Fuzzification Coefficients
Clustering is an unsupervised machine learning method with many practical applications that has gathered extensive research interest. It is a technique of dividing data elements into clusters such that elements in the same cluster are similar. Clustering belongs to the group of unsupervised machine...
Main Authors: | Tran Dinh Khang, Manh-Kien Tran, Michael Fowler |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-08-01
|
Series: | Algorithms |
Subjects: | |
Online Access: | https://www.mdpi.com/1999-4893/14/9/258 |
Similar Items
-
Fuzzy C-Means Clustering Algorithm with Multiple Fuzzification Coefficients
by: Tran Dinh Khang, et al.
Published: (2020-06-01) -
A new Semi-Supervised Intuitionistic Fuzzy C-means Clustering
by: J. Arora, et al.
Published: (2020-01-01) -
Semi-Supervised Deep Fuzzy C-Mean Clustering for Software Fault Prediction
by: Ali Arshad, et al.
Published: (2018-01-01) -
The Empirical Study of Semi-Supervised Deep Fuzzy C-Mean Clustering for Software Fault Prediction
by: Ali Arshad, et al.
Published: (2018-01-01) -
Improving Semi-Supervised Classification using Clustering
by: J. Arora, et al.
Published: (2020-03-01)