Pattern Recognition Publications

patternrecognition.co.za

Return Home

Resources

Publications
Conference papers

Source Code
Classifier source code

Tutorials
Pattern recognition tutorials

Terminology
Definitions of pattern
recognition terms

Pattern Recognition
Applications
A summary of pattern
recognition applications

Classification Applet

Applet
Online implementation of
various classifiers

Data Set Format
Description of the data set
format used for the
classification applet

Example Data Sets
Downloadable data set
examples

Classification Applet
Documentation
Description of the algorithms
used

C.M. van der Walt and E.Barnard, "Data characteristics that determine classifier performance," in Proceedings of the 17th Annual Symposium of the Pattern Recognition Association of South Africa, pp.160-165, Parys, South Africa, November 2006. Available [Online] http://www.patternrecognition.co.za/publications/cvdwalt_data_characteristics_classifiers.pdf

A power point presentation accompanying this article is availavle here.

C.M. van der Walt and E. Barnard, "Data characteristics that determine classifier performance," SAIEE Africa Research Journal, Vol 98 (3), pp 87-93, September 2007. Available [Online] http://www.patternrecognition.co.za/publications/cvdwalt_data_characteristics_SAIEE.pdf

C.M. van der Walt and E. Barnard, "Measures for the characterisation of pattern-recognition data sets," In Proceedings of the 18th Annual Symposium of the Pattern Recognition Association of South Africa (PRASA), pp. 75-78, Pietermaritzburg, South Africa, November 2007. Available [Online] http://www.patternrecognition.co.za/publications/cvdwalt_measures_pattern_recognition_data.pdf

C.M. van der Walt, "Data measures that characterise classification problems," Master's dissertation, Department of Electrical, Electronic and Computer Engineering, University of Pretoria, South Africa, February 2008. Available [Online] http://www.patternrecognition.co.za/publications/cvdwalt_masters_dissertation.pdf

An online implementation of the Naive Bayes, Gaussian, Gaussian Mixture Model, k-nearest neighbours, Decision Tree, Neural Network and Support Vector Machine classifiers is available here.