Dual criteria determination of the number of clusters in data

Kaixun Hua; Dan A. Simovici

doi:10.1109/SYNASC.2018.00040

Dual criteria determination of the number of clusters in data

Kaixun Hua
, Dan A. Simovici

Computer Science

University of Massachusetts Boston

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	201-208
Number of pages	8
ISBN (Electronic)	9781728106250
DOIs	https://doi.org/10.1109/SYNASC.2018.00040
State	Published - Sep 2018
Event	20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018 - Timisoara, Romania Duration: Sep 20 2018 → Sep 23 2018

Publication series

Name	Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018

Conference

Conference	20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018
Country/Territory	Romania
City	Timisoara
Period	9/20/18 → 9/23/18

ASJC Scopus Subject Areas

Computational Theory and Mathematics
Software
Computational Mathematics
Modeling and Simulation
Numerical Analysis

Keywords

Clustering
Cohesion
Entropy
Hypervolume
Pareto front

Access to Document

10.1109/SYNASC.2018.00040

Cite this

Hua, K., & Simovici, D. A. (2018). Dual criteria determination of the number of clusters in data. In Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018 (pp. 201-208). Article 8750738 (Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SYNASC.2018.00040

Dual criteria determination of the number of clusters in data. / Hua, Kaixun; Simovici, Dan A.
Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 201-208 8750738 (Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hua, K & Simovici, DA 2018, Dual criteria determination of the number of clusters in data. in Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018., 8750738, Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 201-208, 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018, Timisoara, Romania, 9/20/18. https://doi.org/10.1109/SYNASC.2018.00040

Hua K, Simovici DA. Dual criteria determination of the number of clusters in data. In Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 201-208. 8750738. (Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018). doi: 10.1109/SYNASC.2018.00040

Hua, Kaixun ; Simovici, Dan A. / Dual criteria determination of the number of clusters in data. Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 201-208 (Proceedings - 2018 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2018).

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Dual criteria determination of the number of clusters in data

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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