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» Gene function prediction using labeled and unlabeled data
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KDD
2009
ACM
150views Data Mining» more  KDD 2009»
15 years 10 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
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KDD
2009
ACM
142views Data Mining» more  KDD 2009»
15 years 10 months ago
Quantification and semi-supervised classification methods for handling changes in class distribution
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...
Jack Chongjie Xue, Gary M. Weiss
GFKL
2005
Springer
141views Data Mining» more  GFKL 2005»
15 years 3 months ago
On External Indices for Mixtures: Validating Mixtures of Genes
Mixture models represent results of gene expression cluster analysis in a more natural way than ’hard’ partitions. This is also true for the representation of gene labels, such...
Ivan G. Costa, Alexander Schliep
GCB
2007
Springer
161views Biometrics» more  GCB 2007»
15 years 4 months ago
High-Precision Function Prediction using Conserved Interactions
: The recent availability of large data sets of protein- protein-interactions (PPIs) from various species offers new opportunities for functional genomics and proteomics. We descri...
Samira Jaeger, Ulf Leser
BMCBI
2008
94views more  BMCBI 2008»
14 years 10 months ago
Conserved co-expression for candidate disease gene prioritization
Background: Genes that are co-expressed tend to be involved in the same biological process. However, co-expression is not a very reliable predictor of functional links between gen...
Martin Oti, Jeroen van Reeuwijk, Martijn A. Huynen...