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» Support Vector Regression Using Mahalanobis Kernels
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ESANN
2006
13 years 10 months ago
Random Forests Feature Selection with K-PLS: Detecting Ischemia from Magnetocardiograms
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
Long Han, Mark J. Embrechts, Boleslaw K. Szymanski...
ICPR
2002
IEEE
14 years 1 months ago
Tangent Distance Kernels for Support Vector Machines
When dealing with pattern recognition problems one encounters different types of a-priori knowledge. It is important to incorporate such knowledge into the classification method ...
Bernard Haasdonk, Daniel Keysers
BMCBI
2007
153views more  BMCBI 2007»
13 years 8 months ago
A new pairwise kernel for biological network inference with support vector machines
Background: Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-pro...
Jean-Philippe Vert, Jian Qiu, William Stafford Nob...
SNPD
2004
13 years 10 months ago
Using extended phylogenetc profiles and support vector machines for protein family classification
We proposed a new approach to compare profiles when the correlations among attributes can be represented as a tree. To account for these correlations, the profile is extended with...
Kishore Narra, Li Liao
EVOW
2006
Springer
14 years 14 days ago
Human Papillomavirus Risk Type Classification from Protein Sequences Using Support Vector Machines
Infection by the human papillomavirus (HPV) is associated with the development of cervical cancer. HPV can be classified to highand low-risk type according to its malignant potenti...
Sun Kim, Byoung-Tak Zhang