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...
Feng Pan, Tim Converse, David Ahn, Franco Salvetti...
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To ...
Among the various types of semantic concepts modeled, events pose the greatest challenge in terms of computational power needed to represent the event and accuracy that can be ach...
Filtering feature selection method (filtering method, for short) is a well-known feature selection strategy in pattern recognition and data mining. Filtering method outperforms ot...
Ou Wu, Haiqiang Zuo, Mingliang Zhu, Weiming Hu, Ju...
: ? Feature Shaping for Linear SVM Classifiers George Forman, Martin Scholz, Shyamsundar Rajaram HP Laboratories HPL-2009-31R1 text classification machine learning, feature weighti...