45 search results - page 2 / 9 » On Feature Selection, Bias-Variance, and Bagging |
100
Voted
KDD
2005
ACM
15 years 5 months ago
2005
ACM
Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
104
Voted
BMCBI
2006
14 years 11 months ago
2006
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...
IDA
2007
Springer
15 years 5 months ago
2007
Springer
Random forests are one of the best performing methods for constructing ensembles. They derive their strength from two aspects: using random subsamples of the training data (as in b...
100
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ISDA
2010
IEEE
14 years 9 months ago
2010
IEEE
Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature sel...
105
Voted
ACCV
2010
Springer
14 years 6 months ago
2010
Springer
Abstract. A tracking-by-detection framework is proposed that combines nearest-neighbor classification of bags of features, efficient subwindow search, and a novel feature selection...