Abstract: The problem of recognition on finite set of events is considered. The generalization ability of classifiers for this problem is studied within the Bayesian approach. The method for non-uniform prior distribution specification on recognition tasks is suggested. It takes into account the assumed degree of intersection between classes. The results of the analysis are applied for pruning of classification trees.

Keywords: classifier generalization ability, Bayesian learning, classification tree pruning.

ACM Classification Keywords: I.5.2 Pattern recognition: classifier design and evaluation

Link:

RECOGNITION ON FINITE SET OF EVENTS: BAYESIAN ANALYSIS OF GENERALIZATION ABILITY AND CLASSIFICATION TREE PRUNING

Vladimir Berikov

http://www.foibg.com/ijita/vol13/ijita13-3-p13.pdf