We propose a novel cost-efficient approach to threshold selection for binary web-page classification problems with imbalanced class distributions. In many binary-classification ta...
We consider the problem of distributed classification of multiple observations of the same object that are collected in an ad-hoc network of vision sensors. Assuming that each sen...
In this work we consider the task of relaxing the i.i.d. assumption in pattern recognition (or classification), aiming to make existing learning algorithms applicable to a wider r...
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Classification is an important problem in data mining. Given a database of records, each with a class label, a classifier generates a concise and meaningful description for each c...