Information theoretic approach for performance evaluation of multi-class assignment systems

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 7697, Issue , 2010, Pages

  Holt, Ryan S ^a   Mastromarino, Peter A ^a   Kao, Edward K ^a   Hurley, Michael B ^a  

^a MIT LINCOLN LABORATORY   (United States)

Author keywords

Classification; Information Theory; Measures of performance; Recognition systems

Indexed keywords

ASSOCIATION PROBABILITY; CONDITIONAL ENTROPY; CONFUSION MATRICES; CONVENTIONAL METHODS; INFORMATION CONTENTS; INFORMATION QUALITY; INFORMATION-THEORETIC APPROACH; INTELLIGENCE , SURVEILLANCE , AND RECONNAISSANCES; MEASURES OF PERFORMANCE; MULTI-CLASS; MUTUAL INFORMATIONS; PARTIAL INFORMATION; PERFORMANCE EVALUATION; RECEIVER OPERATING CHARACTERISTIC CURVES; RECOGNITION SYSTEMS; SIGNAL DETECTION THEORY; TRACKING PROBLEM; TRACKING SYSTEM;

INFORMATION THEORY; SENSORS; SIGNAL DETECTION; SIGNAL PROCESSING; SIGNAL RECEIVERS;

CLASSIFICATION (OF INFORMATION);

EID: 77953491219     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.851019     Document Type: Conference Paper

References (12)

1. Cohen, J., "A coefficient of agreement for nominal scales," Educational and Psychological Measurement 20(1), 37-46 (1960).
2. Fawcett, T., "An introduction to ROC analysis," Pattern Recognition Letters 27, 861-874 (2006).
3. Rand, W. M., "Objective criteria for the evaluation of clustering methods," Journal of the American Statistical Association 66, 846-850 (1971).
4. van Rijsbergen, C. J., [Information Retrieval (2nd edition), Butterworths, London, 112-138 (1979).
5. Berger, J. O., [Statistical Decision Theory and Bayesian Analysis, Springer-Verlag, New York, 46-70 (1980).
6. Witten, I. H., and Frank, E., [Data Mining: Practical Machine Learning Tools and Techniques (2nd edition), Morgan Kaufmann, San Francisco, 143-185 (2005).
7. Chen, H., Chen, G., Blasch, E., Douville, P., and Pham K., "Information theoretic measures for performance evaluation and comparison." 12th International Conference on Information Fusion, 874-881 (2009).
8. Kao, E. K., Daggett, M. P., and Hurley, M. B., "An information theoretic approach for tracker performance evaluation," IEEE 12th International Conference on Computer Vision, 1523-1529 (2009).
9. Cover, T. M., and Thomas, J. A., [Elements of Information Theory, Wiley-Interscience, New York, 20 (1991).
10. Farhadi, A., Tabrizi, M, Endres, I., and Forsyth, D., "A Latent Model of Discriminative Aspect," IEEE 12th International Conference on Computer Vision, 948-955 (2009).
11. Blake, C. L., and Merz, C. J., "UCI repository of machine learning databases," Univ. of California at Irvine, Department of Information and Computer Sciences, http://archive.ics.uci.edu/ml/datasets.html (1998).
12. Duda, R. O., Hart, P. E., and Stork, D. G., [Pattern Classification (2nd edition), Wiley-Interscience, New York, 483-485,2001