354 search results - page 16 / 71 » Learning classifiers from only positive and unlabeled data |
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
This paper presents a novel approach of applying both positive selection and negative selection to supervised learning for anomaly detection. It first learns the patterns of the n...
NAACL
2003
13 years 8 months ago
2003
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
BMCBI
2008
13 years 7 months ago
2008
Background: Predicting a protein's structural or functional class from its amino acid sequence or structure is a fundamental problem in computational biology. Recently, there...
ASUNAM
2010
IEEE
13 years 9 months ago
2010
IEEE
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
ACL
2009
13 years 5 months ago
2009
Modern models of relation extraction for tasks like ACE are based on supervised learning of relations from small hand-labeled corpora. We investigate an alternative paradigm that ...