This paper presents a pattern classification system in which feature extraction and classifier learning are simultaneously carried out not only online but also in one pass where tr...
In many real world applications, the number of examples to learn from is plentiful, but we can only obtain limited information on each individual example. We study the possibiliti...
We investigate the problem of ordering medical events in unstructured clinical narratives by learning to rank them based on their time of occurrence. We represent each medical eve...
Preethi Raghavan, Albert M. Lai, Eric Fosler-Lussi...
This paper describes and analyses the early developmental stages of a community learning network based in an urban community and social service agency. With government funding, th...
Robert Luke, Andrew Clement, Randall Terada, Domin...
Decision trees are a widely used knowledge representation in machine learning. However, one of their main drawbacks is the inherent replication of isomorphic subtrees, as a result...
Christophe Mues, Bart Baesens, Craig M. Files, Jan...