243 search results - page 14 / 49 » Learning Classifiers from Distributed, Ontology-Extended Dat... |
AAAI
1996
13 years 8 months ago
1996
Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competit...
SIGIR
2008
ACM
13 years 7 months ago
2008
ACM
This work presents the use of click graphs in improving query intent classifiers, which are critical if vertical search and general-purpose search services are to be offered in a ...
EMNLP
2009
13 years 5 months ago
2009
Bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retr...
ICML
2003
IEEE
14 years 8 months ago
2003
IEEE
This paper addresses the problem of classification in situations where the data distribution is not homogeneous: Data instances might come from different locations or times, and t...
SDM
2010
SIAM
13 years 9 months ago
2010
SIAM
Lack of labeled training examples is a common problem for many applications. In the same time, there is usually an abundance of labeled data from related tasks. But they have diff...