2161 search results - page 121 / 433 » Learning to classify e-mail |
PKDD
2010
Springer
14 years 11 months ago
2010
Springer
We consider the problem of numerical stability and model density growth when training a sparse linear model from massive data. We focus on scalable algorithms that optimize certain...
183
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PRIB
2010
Springer
14 years 11 months ago
2010
Springer
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
109
Voted
CEAS
2007
Springer
15 years 5 months ago
2007
Springer
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...
125
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CEC
2010
IEEE
15 years 2 months ago
2010
IEEE
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...
88
Voted
COLING
2002
15 years 24 days ago
2002
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...