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BMCBI
2008
115views more  BMCBI 2008»
13 years 7 months ago
Improving peptide-MHC class I binding prediction for unbalanced datasets
Background: Establishment of peptide binding to Major Histocompatibility Complex class I (MHCI) is a crucial step in the development of subunit vaccines and prediction of such bin...
Ana Paula Sales, Georgia D. Tomaras, Thomas B. Kep...
ICDM
2008
IEEE
110views Data Mining» more  ICDM 2008»
14 years 2 months ago
Start Globally, Optimize Locally, Predict Globally: Improving Performance on Imbalanced Data
Class imbalance is a ubiquitous problem in supervised learning and has gained wide-scale attention in the literature. Perhaps the most prevalent solution is to apply sampling to t...
David A. Cieslak, Nitesh V. Chawla
KAIS
2010
144views more  KAIS 2010»
13 years 6 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
KELSI
2004
Springer
14 years 1 months ago
Improving Rule Induction Precision for Automated Annotation by Balancing Skewed Data Sets
There is an overwhelming increase in submissions to genomic databases, posing a problem for database maintenance, especially regarding annotation of fields left blank during submi...
Gustavo E. A. P. A. Batista, Maria Carolina Monard...
DMIN
2009
142views Data Mining» more  DMIN 2009»
13 years 5 months ago
A Combinatorial Fusion Method for Feature Construction
- This paper demonstrates how methods borrowed from information fusion can improve the performance of a classifier by constructing (i.e., fusing) new features that are combinations...
Ye Tian, Gary M. Weiss, D. Frank Hsu, Qiang Ma