A new inverse Nth gravitation based clustering method for data classification

Huarong Xu; Li Hao; Chengjie Jianag; Ejaz Ul Haq

doi:10.1007/978-3-319-59858-1_2

A new inverse N^th gravitation based clustering method for data classification

Huarong Xu^*
, Li Hao
, Chengjie Jianag
, Ejaz Ul Haq

^*Corresponding author for this work

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

Abstract

Data classification is one of the core technologies in the field of pattern recognition and machine learning, which is of great theoretical significance and application value. With the increasing improvement of data acquisition, storage, transmission means and the amount of data, how to extract the essential attribute data from massive data, data accurate classification has become an important research topic. Inverse n^th n order gravitational field is essentially a generalization of the n order in the physics, which can effectively describe the interaction between all the particles in the gravitational field. This paper proposes a new inverse n^th power gravitation (I-n-PG) based clustering method is proposed for data classification. Some randomly generated data samples as well as some well-known classification data sets are used for the verification of the proposed I-n-PG classifier. The experiments show that our proposed I-n-PG classifier performs very well on both of these two test sets.

Original language	English
Title of host publication	Smart Health - International Conference, ICSH 2016, Revised Selected Papers
Editors	Ye Liang, Chunxiao Xing, Yong Zhang
Publisher	Springer Verlag
Pages	9-18
Number of pages	10
ISBN (Print)	9783319598574
DOIs	https://doi.org/10.1007/978-3-319-59858-1_2
State	Published - 2017
Externally published	Yes
Event	International Conference for Smart Health, ICSH 2016 - Haikou, China Duration: 24 Dec 2016 → 25 Dec 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10219 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference for Smart Health, ICSH 2016
Country/Territory	China
City	Haikou
Period	24/12/16 → 25/12/16

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2017.

Keywords

Clustering algorithm
Data classification
Inverse n power gravitation

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-59858-1_2

Cite this

Xu, H., Hao, L., Jianag, C., & Haq, E. U. (2017). A new inverse N^th gravitation based clustering method for data classification. In Y. Liang, C. Xing, & Y. Zhang (Eds.), Smart Health - International Conference, ICSH 2016, Revised Selected Papers (pp. 9-18). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10219 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-59858-1_2

Xu, Huarong ; Hao, Li ; Jianag, Chengjie et al. / A new inverse N^th gravitation based clustering method for data classification. Smart Health - International Conference, ICSH 2016, Revised Selected Papers. editor / Ye Liang ; Chunxiao Xing ; Yong Zhang. Springer Verlag, 2017. pp. 9-18 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{193881cad8cc45b6b2eae37b547f4b91,

title = "A new inverse Nth gravitation based clustering method for data classification",

abstract = "Data classification is one of the core technologies in the field of pattern recognition and machine learning, which is of great theoretical significance and application value. With the increasing improvement of data acquisition, storage, transmission means and the amount of data, how to extract the essential attribute data from massive data, data accurate classification has become an important research topic. Inverse nth n order gravitational field is essentially a generalization of the n order in the physics, which can effectively describe the interaction between all the particles in the gravitational field. This paper proposes a new inverse nth power gravitation (I-n-PG) based clustering method is proposed for data classification. Some randomly generated data samples as well as some well-known classification data sets are used for the verification of the proposed I-n-PG classifier. The experiments show that our proposed I-n-PG classifier performs very well on both of these two test sets.",

keywords = "Clustering algorithm, Data classification, Inverse n power gravitation",

author = "Huarong Xu and Li Hao and Chengjie Jianag and Haq, \{Ejaz Ul\}",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; International Conference for Smart Health, ICSH 2016 ; Conference date: 24-12-2016 Through 25-12-2016",

year = "2017",

doi = "10.1007/978-3-319-59858-1\_2",

language = "English",

isbn = "9783319598574",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "9--18",

editor = "Ye Liang and Chunxiao Xing and Yong Zhang",

booktitle = "Smart Health - International Conference, ICSH 2016, Revised Selected Papers",

address = "Germany",

}

Xu, H, Hao, L, Jianag, C & Haq, EU 2017, A new inverse N^th gravitation based clustering method for data classification. in Y Liang, C Xing & Y Zhang (eds), Smart Health - International Conference, ICSH 2016, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10219 LNCS, Springer Verlag, pp. 9-18, International Conference for Smart Health, ICSH 2016, Haikou, China, 24/12/16. https://doi.org/10.1007/978-3-319-59858-1_2

A new inverse N^th gravitation based clustering method for data classification. / Xu, Huarong; Hao, Li; Jianag, Chengjie et al.
Smart Health - International Conference, ICSH 2016, Revised Selected Papers. ed. / Ye Liang; Chunxiao Xing; Yong Zhang. Springer Verlag, 2017. p. 9-18 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10219 LNCS).

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

TY - GEN

T1 - A new inverse Nth gravitation based clustering method for data classification

AU - Xu, Huarong

AU - Hao, Li

AU - Jianag, Chengjie

AU - Haq, Ejaz Ul

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - Data classification is one of the core technologies in the field of pattern recognition and machine learning, which is of great theoretical significance and application value. With the increasing improvement of data acquisition, storage, transmission means and the amount of data, how to extract the essential attribute data from massive data, data accurate classification has become an important research topic. Inverse nth n order gravitational field is essentially a generalization of the n order in the physics, which can effectively describe the interaction between all the particles in the gravitational field. This paper proposes a new inverse nth power gravitation (I-n-PG) based clustering method is proposed for data classification. Some randomly generated data samples as well as some well-known classification data sets are used for the verification of the proposed I-n-PG classifier. The experiments show that our proposed I-n-PG classifier performs very well on both of these two test sets.

AB - Data classification is one of the core technologies in the field of pattern recognition and machine learning, which is of great theoretical significance and application value. With the increasing improvement of data acquisition, storage, transmission means and the amount of data, how to extract the essential attribute data from massive data, data accurate classification has become an important research topic. Inverse nth n order gravitational field is essentially a generalization of the n order in the physics, which can effectively describe the interaction between all the particles in the gravitational field. This paper proposes a new inverse nth power gravitation (I-n-PG) based clustering method is proposed for data classification. Some randomly generated data samples as well as some well-known classification data sets are used for the verification of the proposed I-n-PG classifier. The experiments show that our proposed I-n-PG classifier performs very well on both of these two test sets.

KW - Clustering algorithm

KW - Data classification

KW - Inverse n power gravitation

UR - https://www.scopus.com/pages/publications/85020388994

U2 - 10.1007/978-3-319-59858-1_2

DO - 10.1007/978-3-319-59858-1_2

M3 - Conference contribution

AN - SCOPUS:85020388994

SN - 9783319598574

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 9

EP - 18

BT - Smart Health - International Conference, ICSH 2016, Revised Selected Papers

A2 - Liang, Ye

A2 - Xing, Chunxiao

A2 - Zhang, Yong

PB - Springer Verlag

T2 - International Conference for Smart Health, ICSH 2016

Y2 - 24 December 2016 through 25 December 2016

ER -

Xu H, Hao L, Jianag C, Haq EU. A new inverse N^th gravitation based clustering method for data classification. In Liang Y, Xing C, Zhang Y, editors, Smart Health - International Conference, ICSH 2016, Revised Selected Papers. Springer Verlag. 2017. p. 9-18. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-59858-1_2