522 search results - page 1 / 105 » Feature selection for ranking using boosted trees |
CIKM
2009
Springer
13 years 11 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
13 years 9 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 4 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
13 years 8 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
12 years 8 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...