Feature selection is often applied to highdimensional data prior to classification learning. Using the same training dataset in both selection and learning can result in socalled ...
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algor...
— A number of large-scale distributed Internet applications could potentially benefit from some level of knowledge about the relative proximity between its participating host no...
Sylvia Ratnasamy, Mark Handley, Richard M. Karp, S...
An “active learning system” will sequentially decide which unlabeled instance to label, with the goal of efficiently gathering the information necessary to produce a good cla...
We present a method for constructing ensembles from libraries of thousands of models. Model libraries are generated using different learning algorithms and parameter settings. For...
Rich Caruana, Alexandru Niculescu-Mizil, Geoff Cre...