114 search results - page 7 / 23 » The use of unlabeled data to improve supervised learning for... |
NIPS
2007
13 years 8 months ago
2007
Semi-supervised methods use unlabeled data in addition to labeled data to construct predictors. While existing semi-supervised methods have shown some promising empirical performa...
IJCAI
2003
13 years 8 months ago
2003
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
FLAIRS
2007
13 years 9 months ago
2007
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome t...
ICCV
2009
IEEE
15 years 10 days ago
2009
IEEE
Random Forests (RFs) have become commonplace
in many computer vision applications. Their
popularity is mainly driven by their high computational
efficiency during both training ...
KDD
2008
ACM
14 years 7 months ago
2008
ACM
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...