522 search results - page 1 / 105 » Feature selection for ranking using boosted trees |
CIKM
2009
Springer
14 years 5 months ago
2009
Springer
Modern search engines have to be fast to satisfy users, so there are hard back-end latency requirements. The set of features useful for search ranking functions, though, continues...
CIKM
2000
Springer
14 years 3 months ago
2000
Springer
RankBoost is a recently proposed algorithm for learning ranking functions. It is simple to implement and has strong justifications from computational learning theory. We describe...
JMLR
2008
13 years 10 months ago
2008
Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
CIKM
2006
Springer
14 years 2 months ago
2006
Springer
It is important yet hard to identify navigational queries in Web search due to a lack of sufficient information in Web queries, which are typically very short. In this paper we st...
ICASSP
2011
IEEE
13 years 2 months ago
2011
IEEE
This paper presents an online feature selection and classification algorithm. The algorithm is implemented for impact acoustics signals to sort hazelnut kernels. The classifier, w...