Using Singularity Exponent in Distance based Classifier

0351724 - ÚI 2011 RIV US eng C - Conference Paper (international conference)
Jiřina, Marcel - Jiřina jr., M.
Using Singularity Exponent in Distance based Classifier.
Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications. Los Alamitos: IEEE, 2010 - (Hassanien, A.; Abraham, A.; Marcelloni, F.; Hagras, H.; Antonelli, M.; Hong, T.), s. 220-224. ISBN 978-1-4244-8135-4.
[ISDA 2010. International Conference on Intelligent Systems Design and Applications /10./. Cairo (EG), 29.11.2010-01.12.2010]
R&D Projects: GA MŠMT 1M0567
Institutional research plan: CEZ:AV0Z10300504
Keywords : singularity exponent * nearest neighbor * classifier
Subject RIV: IN - Informatics, Computer Science

The paper deals with using so called singularity exponent in a classifier that is based on ordered distances of patterns to a given (classified) pattern. The approximation of probability distribution mapping function of the distribution of points from the viewpoint of distances from a given point in a form of a suitable power (exponent) of a distance is presented together with a way how to state it. A classifier utilizing knowledge about explored data distribution in a space and a suggested expression of the exponent is presented. Experimental results on both synthetic and real-life data show interesting behavior (classification accuracy) of the classifier in comparison with other well-known classifiers.
Permanent Link: http://hdl.handle.net/11104/0191414