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BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
13 years 7 months ago
What should be expected from feature selection in small-sample settings
Motivation: High-throughput technologies for rapid measurement of vast numbers of biological variables offer the potential for highly discriminatory diagnosis and prognosis; howev...
Chao Sima, Edward R. Dougherty
RECOMB
2005
Springer
14 years 7 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
ECCV
2010
Springer
14 years 18 days ago
Fast Covariance Computation and Dimensionality Reduction for Sub-Window Features in Images
This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...
EOR
2007
165views more  EOR 2007»
13 years 7 months ago
Adaptive credit scoring with kernel learning methods
Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
Yingxu Yang
PR
2008
115views more  PR 2008»
13 years 7 months ago
Fractional order singular value decomposition representation for face recognition
Face Representation (FR) plays a typically important role in face recognition and methods such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have be...
Jun Liu, Songcan Chen, Xiaoyang Tan