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» Bayes Machines for binary classification
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BMCBI
2010
190views more  BMCBI 2010»
13 years 7 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
ICC
2007
IEEE
141views Communications» more  ICC 2007»
14 years 1 months ago
A Hybrid Model to Detect Malicious Executables
— We present a hybrid data mining approach to detect malicious executables. In this approach we identify important features of the malicious and benign executables. These feature...
Mohammad M. Masud, Latifur Khan, Bhavani M. Thurai...
PAMI
2010
170views more  PAMI 2010»
13 years 6 months ago
On the Decoding Process in Ternary Error-Correcting Output Codes
—A common way to model multiclass classification problems is to design a set of binary classifiers and to combine them. Error-Correcting Output Codes (ECOC) represent a successfu...
Sergio Escalera, Oriol Pujol, Petia Radeva
ACIVS
2006
Springer
13 years 11 months ago
Robust Analysis of Silhouettes by Morphological Size Distributions
We address the topic of real-time analysis and recognition of silhouettes. The method that we propose first produces object features obtained by a new type of morphological operato...
Olivier Barnich, Sébastien Jodogne, Marc Va...
CVPR
2001
IEEE
14 years 9 months ago
Bayesian Learning of Sparse Classifiers
Bayesian approaches to supervised learning use priors on the classifier parameters. However, few priors aim at achieving "sparse" classifiers, where irrelevant/redundant...
Anil K. Jain, Mário A. T. Figueiredo