286 search results - page 2 / 58 » Learning to Classify Texts Using Positive and Unlabeled Data |
BMCBI
2010
13 years 5 months ago
2010
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
ECML
2005
Springer
13 years 10 months ago
2005
Springer
Abstract. We study the problem of learning from positive and unlabeled examples. Although several techniques exist for dealing with this problem, they all assume that positive exam...
ML
2000
ACM
13 years 4 months ago
2000
ACM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
KDD
2002
ACM
14 years 5 months ago
2002
ACM
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...
ICDM
2003
IEEE
13 years 10 months ago
2003
IEEE
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...