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CEAS
2007
Springer
14 years 5 days ago
Online Active Learning Methods for Fast Label-Efficient Spam Filtering
Active learning methods seek to reduce the number of labeled examples needed to train an effective classifier, and have natural appeal in spam filtering applications where trustwo...
D. Sculley
ICDM
2010
IEEE
128views Data Mining» more  ICDM 2010»
13 years 6 months ago
User-Based Active Learning
Active learning has been proven a reliable strategy to reduce manual efforts in training data labeling. Such strategies incorporate the user as oracle: the classifier selects the m...
Christin Seifert, Michael Granitzer
CEC
2010
IEEE
13 years 9 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
IJDAR
2002
116views more  IJDAR 2002»
13 years 7 months ago
Performance evaluation of pattern classifiers for handwritten character recognition
Abstract. This paper describes a performance evaluation study in which some efficient classifiers are tested in handwritten digit recognition. The evaluated classifiers include a s...
Cheng-Lin Liu, Hiroshi Sako, Hiromichi Fujisawa
COLING
2002
13 years 8 months ago
Unsupervised Named Entity Classification Models and their Ensembles
This paper proposes an unsupervised learning model for classifying named entities. This model uses a training set, built automatically by means of a small-scale named entity dicti...
Jae-Ho Kim, In-Ho Kang, Key-Sun Choi