We introduce a method to deal with the problem of learning from imbalanced data sets, where examples of one class significantly outnumber examples of other classes. Our method sel...
In many large e-commerce organizations, multiple data sources are often used to describe the same customers, thus it is important to consolidate data of multiple sources for intell...
This paper presents an integrated rule-based data mining system that is capable of creating rulebased classifiers with web-based user interface from data sets provided by end user...
In this paper, we present a new multiple hypotheses tracking (MHT) approach. Our tracking method is suitable for online applications, because it labels objects at every frame and ...