4. Evaluating Clustering

  1. Zdravko Markov Ph.D.1 and
  2. Daniel T. Larose Ph.D. Professor of Statistics Director2

Published Online: 17 JUL 2006

DOI: 10.1002/9780470108093.ch4

Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage

Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage

How to Cite

Markov, Z. and Larose, D. T. (2007) Evaluating Clustering, in Data Mining the Web: Uncovering Patterns in Web Content, Structure, and Usage, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470108093.ch4

Author Information

  1. 1

    Department of Computer Science, Central Connecticut State University, New Britain, CT, USAwww.cs.ccsu.edu/∼markov/

  2. 2

    Data Mining@CCSU, Department of Mathematical Sciences, Central Connecticut State University, New Britain, CT, USAwww.math.ccsu.edu/larose

Publication History

  1. Published Online: 17 JUL 2006
  2. Published Print: 11 APR 2007

ISBN Information

Print ISBN: 9780471666554

Online ISBN: 9780470108093

SEARCH

Keywords:

  • evaluating clustering approaches;
  • probabilistic criterion functions;
  • MDL-based model and feature evaluation

Summary

This chapter contains sections titled:

  • Approaches to Evaluating Clustering

  • Similarity-Based Criterion Functions

  • Probabilistic Criterion Functions

  • MDL-Based Model and Feature Evaluation

  • Classes-to-Clusters Evaluation

  • Precision, Recall, and F-Measure

  • Entropy

  • References

  • Exercises