The evaluation of classifier performance in a cost-sensitive setting is straightforward if the operating conditions (misclassification costs and class distributions) are fixed and known. When this is not the case, evaluation requires a method of visualizing classifier performance across the full range of possible operating conditions. This talk outlines the most important requirements for cost-...

brain mr images tissue segmentation is one of the most important parts of the clinical diagnostic tools. pixel classification methods have been frequently used in the image segmentation with two supervised and unsupervised approaches up to now. supervised segmentation methods lead to high accuracy but they need a large amount of labeled data, which is hard, expensive and slow to obtain. moreove...

The performance of a recognition system depends upon the classifiers used for classification purpose. Powerful is the discrimination ability of a classifier, better is its recognition performance. The generalization ability of a classifier is measured on the basis of its performance in classifying the test patterns. There are various factors which affect generalization. Moreover, the feature ex...

Cross Validation (CV) is widely used to measure the performance of a classifier. The main purpose of this study is to explore the behavior of CV in tree-based models. We report experimental studies that compare a cross-validated tree classifier with an oracle classifier that is ideally derived on the knowledge of underlying distributions. The main observation of this study indicates that the di...