Item Infomation
Title: |
Fuzzy clustering with entropy regularization for interval-valued data with an application to scientific journal citations |
Authors: |
Pierpaolo, D’Urso Livia De, Giovanni Leonardo Salvatore, Alaimo |
Issue Date: |
2023 |
Publisher: |
Springer |
Abstract: |
In recent years, the research of statistical methods to analyze complex structures of data has increased. In particular, a lot of attention has been focused on the interval-valued data. In a classical cluster analysis framework, an interesting line of research has focused on the clustering of interval-valued data based on fuzzy approaches. Following the partitioning around medoids fuzzy approach research line, a new fuzzy clustering model for interval-valued data is suggested. In particular, we propose a new model based on the use of the entropy as a regularization function in the fuzzy clustering criterion. The model uses a robust weighted dissimilarity measure to smooth noisy data and weigh the center and radius components of the interval-valued data, respectively. |
Description: |
CC BY |
URI: |
https://link.springer.com/article/10.1007/s10479-023-05180-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8482 |
Appears in Collections |
OER - Kinh tế và Quản lý |
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