A data reduction approach for resolving the imbalanced data issue in functional genomics

@article{Yoon2007ADR,
  title={A data reduction approach for resolving the imbalanced data issue in functional genomics},
  author={Kihoon Yoon and Stephen Kwek},
  journal={Neural Computing and Applications},
  year={2007},
  volume={16},
  pages={295-306}
}
Learning from imbalanced data occurs frequently in many machine learning applications. One positive example to thousands of negative instances is common in scientific applications. Unfortunately, traditional machine learning techniques often treat rare instances as noise. One popular approach for this difficulty is to resample the training data. However, this results in high false positive predictions. Hence, we propose preprocessing training data by partitioning them into clusters. This… CONTINUE READING
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