This paper investigates how the splitting criteria and pruning methods of decision tree learning algorithms are influenced by misclassification costs or changes to the class distr...
We propose a simple, novel and yet effective method for building and testing decision trees that minimizes the sum of the misclassification and test costs. More specifically, we f...
Charles X. Ling, Qiang Yang, Jianning Wang, Shicha...
The presence of asymmetry in the misclassification costs or class prevalences is a common occurrence in the pattern classification domain. While much interest has been devoted to ...
Receiver Operating Characteristics (ROC) graphs are a useful technique for organizing classifiers and visualizing their performance. ROC graphs have been used in cost-sensitive le...
We present the notion of Ranking for evaluation of two-class classifiers. Ranking is based on using the ordering information contained in the output of a scoring model, rather tha...