We discuss multiclass-multilabel classification problems in which the set of classes is extremely large. Most existing multiclass-multilabel learning algorithms expect to observe ...
In this paper, a new method of composing a multiclass classifier using pairwise classifiers is proposed. A “Resemblance Model” is exploited to calculate a posteriori probabili...
Background: Gene expression microarray is a powerful technology for genetic profiling diseases and their associated treatments. Such a process involves a key step of biomarker ide...
Zhipeng Cai, Randy Goebel, Mohammad R. Salavatipou...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
We propose a highly efficient framework for penalized likelihood kernel methods applied to multiclass models with a large, structured set of classes. As opposed to many previous a...