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» Informative sampling for large unbalanced data sets
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BMCBI
2011
14 years 5 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
RECOMB
2010
Springer
15 years 8 months ago
Hierarchical Generative Biclustering for MicroRNA Expression Analysis
Clustering methods are a useful and common first step in gene expression studies, but the results may be hard to interpret. We bring in explicitly an indicator of which genes tie ...
José Caldas, Samuel Kaski
ICDM
2005
IEEE
135views Data Mining» more  ICDM 2005»
15 years 7 months ago
Bit Reduction Support Vector Machine
Abstract— Support vector machines are very accurate classifiers and have been widely used in many applications. However, the training and to a lesser extent prediction time of s...
Tong Luo, Lawrence O. Hall, Dmitry B. Goldgof, And...
120
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PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
15 years 8 months ago
Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling
This paper presents an interdisciplinary investigation of statistical information retrieval (IR) techniques for protein identification from tandem mass spectra, a challenging probl...
Yiming Yang, Abhay Harpale, Subramaniam Ganapathy
TNN
2010
154views Management» more  TNN 2010»
14 years 8 months ago
Discriminative semi-supervised feature selection via manifold regularization
We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number ...
Zenglin Xu, Irwin King, Michael R. Lyu, Rong Jin