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IJON
2010
181views more  IJON 2010»
14 years 8 months ago
Active learning with extremely sparse labeled examples
An active learner usually assumes there are some labeled data available based on which a moderate classifier is learned and then examines unlabeled data to manually label the mos...
Shiliang Sun, David R. Hardoon
CEC
2010
IEEE
14 years 7 months ago
Active Learning Genetic programming for record deduplication
The great majority of genetic programming (GP) algorithms that deal with the classification problem follow a supervised approach, i.e., they consider that all fitness cases availab...
Junio de Freitas, Gisele L. Pappa, Altigran Soares...
ECIR
2009
Springer
14 years 7 months ago
Active Learning Strategies for Multi-Label Text Classification
Abstract. Active learning refers to the task of devising a ranking function that, given a classifier trained from relatively few training examples, ranks a set of additional unlabe...
Andrea Esuli, Fabrizio Sebastiani
AI
2002
Springer
14 years 9 months ago
Learning cost-sensitive active classifiers
Most classification algorithms are "passive", in that they assign a class label to each instance based only on the description given, even if that description is incompl...
Russell Greiner, Adam J. Grove, Dan Roth
DGO
2003
111views Education» more  DGO 2003»
14 years 11 months ago
Assessing the Usefulness and Usability of Online Learning Activities: MapStats for Kids
MapStats for Kids is concerned with the development of online learning activities based on data from the FedStats web portal. The development of these web applications requires th...
Sven Fuhrmann, John Bosley, Roger Downs, Mark Gahe...