Bayesian network classifiers have been widely used for classification problems. Given a fixed Bayesian network structure, parameters learning can take two different approaches: ge...
Jiang Su, Harry Zhang, Charles X. Ling, Stan Matwi...
Modern classification applications necessitate supplementing the few available labeled examples with unlabeled examples to improve classification performance. We present a new tra...
Abstract. Many supervised machine learning tasks can be cast as multi-class classification problems. Support vector machines (SVMs) excel at binary classification problems, but the...
A principally new approach to the classifications of nucleotide sequences based on the "natural" classification concept is proposed. As a result of "natural" c...
Eugenii E. Vityaev, K. A. Lapardin, I. V. Khomiche...
This paper describes an approach for detecting early cognitive loss using medication adherence behavior. We investigate the discriminative power of a comprehensive set of recurren...
Yonghong Huang, Deniz Erdogmus, Zhengdong Lu, Todd...