PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The performance of a new hybrid classifier based on boxes and nearest neighbours.
Martin Anthony and Joel Ratsaby
In: International Symposium on Artificial Intelligence and Mathematics 2012, 9-11 January 2012, Fort Lauderdale, Florida.


In this paper we present a new type of binary classifier defined on the unit cube. This classifier combines some of the aspects of the standard methods that have been used in the logical analysis of data (LAD) and geometric classifiers, with a nearest-neighbor paradigm. We assess the predictive performance of the new classifier in learning from a sample, obtaining generalization error bounds that improve as the `sample width' of the classifier increases.

EPrint Type:Conference or Workshop Item (Talk)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
ID Code:8581
Deposited By:Martin Anthony
Deposited On:12 February 2012