522 search results - page 7 / 105 » Feature selection for ranking using boosted trees |
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ESANN
2006
14 years 11 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
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ICML
2001
IEEE
15 years 10 months ago
2001
IEEE
In this paper, we examine the advantages and disadvantages of filter and wrapper methods for feature selection and propose a new hybrid algorithm that uses boosting and incorporat...
IR
2010
14 years 8 months ago
2010
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
CVPR
2006
IEEE
15 years 11 months ago
2006
IEEE
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
SEBD
2008
14 years 11 months ago
2008
Abstract. Feature selection is an important task in data mining because it allows to reduce the data dimensionality and eliminates the noisy variables. Traditionally, feature selec...