article

Fuzzy clustering of intuitionistic fuzzy data

Authors:

Nikos Pelekis,

Dimitris K. Iakovidis,

Evangelos E. Kotsifakos,

Ioannis KopanakisAuthors Info & Claims

International Journal of Business Intelligence and Data Mining, Volume 3, Issue 1

Pages 45 - 65

https://doi.org/10.1504/IJBIDM.2008.017975

Published: 01 April 2008 Publication History

Abstract

Challenged by real-world clustering problems this paper proposes a novel fuzzy clustering scheme of datasets produced in the context of intuitionistic fuzzy set theory. More specifically, we introduce a variant of the Fuzzy C-Means (FCM) clustering algorithm that copes with uncertainty and a similarity measure between intuitionistic fuzzy sets, which is appropriately integrated in the clustering algorithm. We describe an intuitionistic fuzzification of colour digital images upon which we applied the proposed scheme. The experimental evaluation of the proposed scheme shows that it can be more efficient and more effective than the well-established FCM algorithm, opening perspectives for various applications.

Cited By

View all

Singh CRanade SKaur DBala A(2024)A kernelized-bias-corrected fuzzy C-means approach with moment domain filtering for segmenting brain magnetic resonance imagesSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09379-z28:3(1909-1933)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s00500-023-09379-z
Solanki RKumar D(2023)Probabilistic intuitionistic fuzzy c-means algorithm with spatial constraint for human brain MRI segmentationMultimedia Tools and Applications10.1007/s11042-023-14512-z82:22(33663-33692)Online publication date: 7-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14512-z
Sovatzidi GVasilakakis MIakovidis D(2022)IF3: An Interpretable Feature Fusion Framework for Lesion Risk Assessment Based on Auto-constructed Fuzzy Cognitive MapsCancer Prevention Through Early Detection10.1007/978-3-031-17979-2_8(77-86)Online publication date: 22-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-17979-2_8
Show More Cited By

Index Terms

Fuzzy clustering of intuitionistic fuzzy data
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic
  2. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Clustering and classification
  2. Information systems applications
    1. Data mining
      1. Clustering

Recommendations

A novel similarity measure between intuitionistic fuzzy sets based on the centroid points of transformed fuzzy numbers with applications to pattern recognition

In this paper, we propose a new similarity measure between intuitionistic fuzzy values based on the centroid points of transformed right-angled triangular fuzzy numbers. We also prove some properties of the proposed similarity measure between ...
I-fuzzy partitions for representing clustering uncertainties
ICAISC'10: Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I

In a recent paper we introduced intuitionistic fuzzy partitions or interval-valued fuzzy partitions as a way to represent the uncertainty of fuzzy clustering. In this paper we reconsider these definitions so that these fuzzy partitions can be used to ...
A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI image

Fuzzy c-means (FCM) is one of the prominent method utilized for medical image segmentation. In literature intuitionistic fuzzy c-means (IFCM) is suggested which is based on intuitionistic fuzzy sets (IFSs) theory to handle uncertainty and vagueness ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image International Journal of Business Intelligence and Data Mining

International Journal of Business Intelligence and Data Mining Volume 3, Issue 1

April 2008

114 pages

ISSN:1743-8195

EISSN:1743-8187

Issue’s Table of Contents

Publisher

Inderscience Publishers

Geneva 15, Switzerland

Publication History

Published: 01 April 2008

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

25
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 25 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Singh CRanade SKaur DBala A(2024)A kernelized-bias-corrected fuzzy C-means approach with moment domain filtering for segmenting brain magnetic resonance imagesSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-09379-z28:3(1909-1933)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1007/s00500-023-09379-z
Solanki RKumar D(2023)Probabilistic intuitionistic fuzzy c-means algorithm with spatial constraint for human brain MRI segmentationMultimedia Tools and Applications10.1007/s11042-023-14512-z82:22(33663-33692)Online publication date: 7-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14512-z
Sovatzidi GVasilakakis MIakovidis D(2022)IF3: An Interpretable Feature Fusion Framework for Lesion Risk Assessment Based on Auto-constructed Fuzzy Cognitive MapsCancer Prevention Through Early Detection10.1007/978-3-031-17979-2_8(77-86)Online publication date: 22-Sep-2022
https://dl.acm.org/doi/10.1007/978-3-031-17979-2_8
Zhang DMa YZhao HYang X(2021)Neutrosophic Clustering Algorithm Based on Sparse Regular Term ConstraintComplexity10.1155/2021/66578492021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6657849
Wu CHuang CZhang J(2021)Intuitionistic fuzzy information-driven total Bregman divergence fuzzy clustering with multiple local information constraints for image segmentationThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-021-02319-839:1(149-181)Online publication date: 12-Nov-2021
https://dl.acm.org/doi/10.1007/s00371-021-02319-8
Ma RZeng WSong GYin QXu Z(2021)Pythagorean fuzzy C‐means algorithm for image segmentationInternational Journal of Intelligent Systems10.1002/int.2233936:3(1223-1243)Online publication date: 28-Jan-2021
https://dl.acm.org/doi/10.1002/int.22339
Jin DBai X(2020)Distribution Information Based Intuitionistic Fuzzy Clustering for Infrared Ship SegmentationIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2019.291780928:8(1557-1571)Online publication date: 3-Aug-2020
https://dl.acm.org/doi/10.1109/TFUZZ.2019.2917809
Kumar DAgrawal RSingh Kirar J(2019)Intuitionistic Fuzzy Clustering Method with Spatial Information for MRI Image Segmentation2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)10.1109/FUZZ-IEEE.2019.8858865(1-7)Online publication date: 23-Jun-2019
https://dl.acm.org/doi/10.1109/FUZZ-IEEE.2019.8858865
Kumar DVerma HMehra AAgrawal R(2019)A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI imageMultimedia Tools and Applications10.1007/s11042-018-5954-078:10(12663-12687)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1007/s11042-018-5954-0
Kumar DAgrawal RVerma H(2019)Kernel intuitionistic fuzzy entropy clustering for MRI image segmentationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-04169-y24:6(4003-4026)Online publication date: 27-Jun-2019
https://dl.acm.org/doi/10.1007/s00500-019-04169-y
Show More Cited By

Abstract

Cited By

Index Terms

Recommendations

A novel similarity measure between intuitionistic fuzzy sets based on the centroid points of transformed fuzzy numbers with applications to pattern recognition

I-fuzzy partitions for representing clustering uncertainties

A modified intuitionistic fuzzy c-means clustering approach to segment human brain MRI image

Comments

Information

Published In

Publisher

Publication History

Author Tags

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations