Data Clustering: An Approach for Evaluating the Adequate Number of Groups in Partitioned Techniques
Abstract
The partitioned clustering techniques, such as k-means, have advantages in applications involving a large amount of data, but a particularity of this type of clustering is to establish a priori the number of input groups (k). So in practice, it is necessary to repeat the test by establishing different numbers of groups, choosing the solution that best suits the objective of the problem. Therefore, to validate the results obtained it is necessary to have validation mechanisms that allow evaluating the formation of the groups appropriately. An evaluation strategy is through validation indexes that help determine if the formation of the groups is adequate. These methods are based on estimates that identify how compact or separate the formed groups are. This paper presents validation indexes used as a strategy to determine the number of relevant groups. The results obtained indicate that this evaluation approach guarantees an adequate way the determination of the desired number of groups.
Full Text: PDF DOI: 10.15640/jcsit.v5n1a3
Abstract
The partitioned clustering techniques, such as k-means, have advantages in applications involving a large amount of data, but a particularity of this type of clustering is to establish a priori the number of input groups (k). So in practice, it is necessary to repeat the test by establishing different numbers of groups, choosing the solution that best suits the objective of the problem. Therefore, to validate the results obtained it is necessary to have validation mechanisms that allow evaluating the formation of the groups appropriately. An evaluation strategy is through validation indexes that help determine if the formation of the groups is adequate. These methods are based on estimates that identify how compact or separate the formed groups are. This paper presents validation indexes used as a strategy to determine the number of relevant groups. The results obtained indicate that this evaluation approach guarantees an adequate way the determination of the desired number of groups.
Full Text: PDF DOI: 10.15640/jcsit.v5n1a3
Browse Journals
Journal Policies
Information
Useful Links
- Call for Papers
- Submit Your Paper
- Publish in Your Native Language
- Subscribe the Journal
- Frequently Asked Questions
- Contact the Executive Editor
- Recommend this Journal to Librarian
- View the Current Issue
- View the Previous Issues
- Recommend this Journal to Friends
- Recommend a Special Issue
- Comment on the Journal
- Publish the Conference Proceedings
Latest Activities
Resources
Visiting Status
Today | 177 |
Yesterday | 122 |
This Month | 3788 |
Last Month | 6586 |
All Days | 1470501 |
Online | 12 |