Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. KMITL
  3. Publication
  4. Using a Learning Classifier System for clustering
Loading...
Thumbnail Image

Using a Learning Classifier System for clustering

Author(s)
Tamee, Kreangsak
Bull, Larry
Pinngern, Ouen
Rojanavasu, Pornthep
Srinil, Phaitoon
Date Issued
December 1, 2006
Type
Conference Paper
DOI
10.1109/ISCIT.2006.339884
Abstract
This paper presents a novel approach to clustering using a simple accuracy-based Learning Classifier System. Our approach achieves this by exploiting the evolutionary computing and reinforcement learning techniques inherent to such systems. The purpose of the work is to develop an approach to learning rules which accurately describe clusters without prior assumptions as to their number within a given dataset. Favourable comparisons to the commonly used k-means algorithm are demonstrated on a number of datasets. © 2006 IEEE.
Citation
2006 International Symposium on Communications and Information Technologies Iscit, 43-48, 2006
Metrics
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your Institution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback