Most machine learning algorithms share the following drawback: they only output bare predictions but not the con dence in those predictions. In the 1960s algorithmic information t...
AdaCost, a variant of AdaBoost, is a misclassification cost-sensitive boosting method. It uses the cost of misclassifications to update the training distribution on successive boo...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip...
: Numerical function approximation over a Boolean domain is a classical problem with wide application to data modeling tasks and various forms of learning. A great many function ap...
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, p...
This paper considers approaches which rerank the output of an existing probabilistic parser. The base parser produces a set of candidate parses for each input sentence, with assoc...