Big-data clustering with interval type-2 fuzzy uncertainty modeling in gene expression datasets

2019 ◽  
Vol 77 ◽  
pp. 268-282 ◽  
Author(s):  
Amit K. Shukla ◽  
Pranab K. Muhuri
Keyword(s):  
Gene Expression ◽  
Big Data ◽  
Data Clustering ◽  
Uncertainty Modeling ◽  
Fuzzy Uncertainty ◽  
Interval Type

Interpretable interval type-2 fuzzy predicates for data clustering: A new automatic generation method based on self-organizing maps

2017 ◽  
Vol 133 ◽  
pp. 234-254 ◽  
Author(s):  
Diego S. Comas ◽  
Juan I. Pastore ◽  
Agustina Bouchet ◽  
Virginia L. Ballarin ◽  
Gustavo J. Meschino
Keyword(s):  
Data Clustering ◽  
Automatic Generation ◽  
Self Organizing Maps ◽  
Interval Type ◽  
Self Organizing

scholarly journals An Interval Type-2 Possibilistic C-Means Clustering Algorithm and Its Application

2021 ◽  
Vol 2132 (1) ◽  
pp. 012016
Author(s):  
Haihua Xing ◽  
Huannan Chen ◽  
Hongyan Lin ◽  
Xinghui Wu
Keyword(s):  
Image Segmentation ◽  
Fuzzy Sets ◽  
Clustering Algorithm ◽  
High Order ◽  
Data Sets ◽  
Fuzzy Uncertainty ◽  
Penalty Factor ◽  
Interval Type

Abstract In this paper, we aim at the fuzzy uncertainty caused by noise in pattern data. The advantages of PCM algorithm to deal with noise and interval type-2 fuzzy sets to deal with high-order uncertainties are used, respectively. An interval type-2 probability C-means clustering (IT2-PCM) based on penalty factor is proposed. The performance of the algorithm is evaluated by two sets of data sets and two groups of images segmentation experiments. The results show that IT2-PCM algorithm can assign proper membership degrees to clustering samples with noise, and it can detect noise points effectively, and it has good performance in image segmentation.

Veracity handling and instance reduction in big data using interval type-2 fuzzy sets

2020 ◽  
Vol 88 ◽  
pp. 103315 ◽  
Author(s):  
Amit K. Shukla ◽  
Megha Yadav ◽  
Sandeep Kumar ◽  
Pranab K. Muhuri
Keyword(s):  
Big Data ◽  
Fuzzy Sets ◽  
Instance Reduction ◽  
Interval Type

Discovering knowledge from data clustering using automatically-defined interval type-2 fuzzy predicates

2017 ◽  
Vol 68 ◽  
pp. 136-150 ◽  
Author(s):  
Diego S. Comas ◽  
Gustavo J. Meschino ◽  
Ann Nowé ◽  
Virginia L. Ballarin
Keyword(s):  
Data Clustering ◽  
Interval Type
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