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BIOINFORMATICS
2006
92views more  BIOINFORMATICS 2006»
15 years 7 days 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
109
Voted
RECOMB
2005
Springer
16 years 14 days 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
15 years 5 months 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...
119
Voted
EOR
2007
165views more  EOR 2007»
15 years 4 days 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»
15 years 3 days 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