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» A Distance-Based Over-Sampling Method for Learning from Imba...
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MICAI
2007
Springer
14 years 2 months ago
Taking Advantage of the Web for Text Classification with Imbalanced Classes
A problem of supervised approaches for text classification is that they commonly require high-quality training data to construct an accurate classifier. Unfortunately, in many real...
Rafael Guzmán-Cabrera, Manuel Montes-y-G&oa...
CVPR
2008
IEEE
14 years 10 months ago
Active microscopic cellular image annotation by superposable graph transduction with imbalanced labels
Systematic content screening of cell phenotypes in microscopic images has been shown promising in gene function understanding and drug design. However, manual annotation of cells ...
Jun Wang, Shih-Fu Chang, Xiaobo Zhou, Stephen T. C...
KELSI
2004
Springer
14 years 2 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...
PROMISE
2010
13 years 3 months ago
On the value of learning from defect dense components for software defect prediction
BACKGROUND: Defect predictors learned from static code measures can isolate code modules with a higher than usual probability of defects. AIMS: To improve those learners by focusi...
Hongyu Zhang, Adam Nelson, Tim Menzies
MCS
2010
Springer
13 years 6 months ago
Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers
Multilabel classification is a challenging research problem in which each instance is assigned to a subset of labels. Recently, a considerable amount of research has been concerned...
Muhammad Atif Tahir, Josef Kittler, Krystian Mikol...