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» A Case Study for Learning from Imbalanced Data Sets
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BMCBI
2011
14 years 9 months ago
Cell Subset Prediction for Blood Genomic Studies
Background: Genome-wide transcriptional profiling of patient blood samples offers a powerful tool to investigate underlying disease mechanisms and personalized treatment decisions...
Christopher R. Bolen, Mohamed Uduman, Steven H. Kl...
ISPW
2008
IEEE
16 years 14 days ago
Accurate Estimates without Calibration?
Most process models calibrate their internal settings using historical data. Collecting this data is expensive, tedious, and often an incomplete process. Is it possible to make acc...
Tim Menzies, Oussama El-Rawas, Barry W. Boehm, Ray...
SAC
2009
ACM
16 years 27 days ago
Combining statistics and semantics via ensemble model for document clustering
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
BMCBI
2010
182views more  BMCBI 2010»
15 years 6 months ago
L2-norm multiple kernel learning and its application to biomedical data fusion
Background: This paper introduces the notion of optimizing different norms in the dual problem of support vector machines with multiple kernels. The selection of norms yields diff...
Shi Yu, Tillmann Falck, Anneleen Daemen, Lé...
RSEISP
2007
Springer
16 years 6 days ago
Checking Brain Expertise Using Rough Set Theory
Most information about the external world comes from our visual brain. However, it is not clear how this information is processed. We will analyze brain responses using machine lea...
Andrzej W. Przybyszewski