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RECOMB
2005
Springer
16 years 3 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...
EUSFLAT
2003
206views Fuzzy Logic» more  EUSFLAT 2003»
15 years 1 months ago
Analysis of multi-product break-even with uncertain information
We revise the classic methodology to find the multi-product break-even point. In the current paper we propose a solution to the problem under uncertainty conditions, based on DurÃ...
Luisa L. Lazzari, María Silvia Moriñ...
CVPR
2003
IEEE
16 years 1 months ago
Kullback-Leibler Boosting
In this paper, we develop a general classification framework called Kullback-Leibler Boosting, or KLBoosting. KLBoosting has following properties. First, classification is based o...
Ce Liu, Heung-Yeung Shum
PR
2007
139views more  PR 2007»
14 years 11 months ago
Learning the kernel matrix by maximizing a KFD-based class separability criterion
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
Dit-Yan Yeung, Hong Chang, Guang Dai
BMCBI
2010
135views more  BMCBI 2010»
14 years 12 months ago
Simple and flexible classification of gene expression microarrays via Swirls and Ripples
Background: A simple classification rule with few genes and parameters is desirable when applying a classification rule to new data. One popular simple classification rule, diagon...
Stuart G. Baker