Name
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. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-59858-1_2 | Lecture Notes in Computer Science |
Keywords | DocType | Volume |
Data classification,Inverse nth power gravitation,Clustering algorithm | Conference | 10219 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huarong Xu | 1 | 17 | 4.17 |
| Li Hao | 2 | 64 | 16.50 |
| Chengjie Jianag | 3 | 0 | 0.34 |
| Ejaz Ul Haq | 4 | 0 | 1.69 |