An Advanced Clustering Algorithm (ACA) for Clustering Large Data Set to Achieve High Dimensionality

Article ID

CSTSDER82XA

An Advanced Clustering Algorithm (ACA) for Clustering Large Data Set to Achieve High Dimensionality

Aman Toor
Aman Toor
DOI

Abstract

Cluster analysis method is one of the main analytical methods in data mining; this method of clustering algorithm will influence the clustering results directly. This paper proposes an Advanced Clustering Algorithm in order to solve this question, requiring a simple data structure to store some information [1] in every iteration, which is to be used in the next iteration. The Advanced Clustering Algorithm method avoids computing the distance of each data object to the cluster centers repeat, saving the running time. Experimental results show that the Advanced Clustering Algorithm method can effectively improve the speed of clustering and accuracy, reducing the computational complexity of the traditional algorithm. This paper includes Advanced Clustering Algorithm (ACA) and describes the experimental results and conclusions through experimenting with academic data sets.

An Advanced Clustering Algorithm (ACA) for Clustering Large Data Set to Achieve High Dimensionality

Cluster analysis method is one of the main analytical methods in data mining; this method of clustering algorithm will influence the clustering results directly. This paper proposes an Advanced Clustering Algorithm in order to solve this question, requiring a simple data structure to store some information [1] in every iteration, which is to be used in the next iteration. The Advanced Clustering Algorithm method avoids computing the distance of each data object to the cluster centers repeat, saving the running time. Experimental results show that the Advanced Clustering Algorithm method can effectively improve the speed of clustering and accuracy, reducing the computational complexity of the traditional algorithm. This paper includes Advanced Clustering Algorithm (ACA) and describes the experimental results and conclusions through experimenting with academic data sets.

Aman Toor
Aman Toor

No Figures found in article.

Aman Toor. 2014. “. Global Journal of Computer Science and Technology – C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C2): .

Download Citation

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Issue Cover
GJCST Volume 14 Issue C2
Pg. 71- 74
Classification
Not Found
Article Matrices
Total Views: 9000
Total Downloads: 2157
2026 Trends
Research Identity (RIN)
Related Research
Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

An Advanced Clustering Algorithm (ACA) for Clustering Large Data Set to Achieve High Dimensionality

Aman Toor
Aman Toor

Research Journals