24 search results - page 3 / 5 » Ensemble Learning with Active Example Selection for Imbalanc... |
NLE
2008
13 years 5 months ago
2008
For complex tasks such as parse selection, the creation of labelled training sets can be extremely costly. Resource-efficient schemes for creating informative labelled material mu...
Publication
One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...
ML
2006
ACM
13 years 5 months ago
2006
ACM
Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. A common way to measure performance in these domains is to use precision and recall i...
BMCBI
2010
13 years 5 months ago
2010
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
TASLP
2010
12 years 12 months ago
2010
To solve the knowledge bottleneck problem, active learning has been widely used for its ability to automatically select the most informative unlabeled examples for human annotation...