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» Evaluating learning algorithms and classifiers
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SAC
2005
ACM
15 years 9 months ago
Comparing approaches to predict transmembrane domains in protein sequences
There are today several systems for predicting transmembrane domains in membrane protein sequences. As they are based on different classifiers as well as different pre- and post-p...
Paul Davidsson, Johan Hagelbäck, Kenny Svenss...
132
Voted
GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
15 years 10 months ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifical...
Robert Elliott Smith, Max Kun Jiang
ISCIS
2005
Springer
15 years 9 months ago
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Zeki Erdem, Robi Polikar, Nejat Yumusak, Fikret S....
112
Voted
ICML
2007
IEEE
16 years 4 months ago
Quadratically gated mixture of experts for incomplete data classification
We introduce quadratically gated mixture of experts (QGME), a statistical model for multi-class nonlinear classification. The QGME is formulated in the setting of incomplete data,...
Xuejun Liao, Hui Li, Lawrence Carin
ICIP
2008
IEEE
16 years 5 months ago
Cross-domain learning methods for high-level visual concept classification
Exploding amounts of multimedia data increasingly require automatic indexing and classification, e.g. training classifiers to produce high-level features, or semantic concepts, ch...
Wei Jiang, Eric Zavesky, Shih-Fu Chang, Alexander ...