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» Rule extraction from linear support vector machines
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ICASSP
2011
IEEE
14 years 1 months ago
Online Kernel SVM for real-time fMRI brain state prediction
The Support Vector Machine (SVM) methodology is an effective, supervised, machine learning method that gives stateof-the-art performance for brain state classification from funct...
Yongxin Taylor Xi, Hao Xu, Ray Lee, Peter J. Ramad...
BMCBI
2007
157views more  BMCBI 2007»
14 years 9 months ago
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...
IMSCCS
2007
IEEE
15 years 3 months ago
Asymmetric Bagging and Feature Selection for Activities Prediction of Drug Molecules
Background: Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cy...
Guo-Zheng Li, Hao-Hua Meng, Mary Qu Yang, Jack Y. ...
ERCIMDL
2006
Springer
204views Education» more  ERCIMDL 2006»
15 years 1 months ago
Comparing and Combining Two Approaches to Automated Subject Classification of Text
A machine-learning and a string-matching approach to automated subject classification of text were compared, as to their performance, advantages and downsides. The former approach ...
Koraljka Golub, Anders Ardö, Dunja Mladenic, ...
AIME
2009
Springer
14 years 10 months ago
Learning Approach to Analyze Tumour Heterogeneity in DCE-MRI Data During Anti-cancer Treatment
Abstract. The paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of Dynamic Contrast-Enhan...
Alessandro Daducci, Umberto Castellani, Marco Cris...