Classifier Generalization Ability Bayesian Learning Classification Tree Pruning
Institute of Information Theories and Applications FOI ITHEA
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.