Classification problems with uneven class distributions present several difficulties during the training as well as during the evaluation process of classifiers. A classification ...
Sophia Daskalaki, Ioannis Kopanas, Nikolaos M. Avo...
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...
For large, real-world inductive learning problems, the number of training examples often must be limited due to the costs associated with procuring, preparing, and storing the tra...
In this paper, we focus on methodology of finding a classifier with a minimal cost in presence of additional performance constraints. ROCCH analysis, where accuracy and cost are i...
The purpose of this research is to propose an appropriate classification approach to improving the effectiveness of spam filtering on the issue of skewed class distributions. A cl...