期刊
JOURNAL OF MOLECULAR GRAPHICS & MODELLING
卷 72, 期 -, 页码 256-265出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jmgm.2017.01.008
关键词
Aggregated conformal prediction; Imbalanced datasets; QSAR; Signature descriptors; Support vector machines
类别
资金
- Stockholm County Council, Knut & Alice Wallenberg Foundation
- Swedish Research Council FORMAS
Aggregated Conformal Prediction is used as an effective alternative to other, more complicated and/or ambiguous methods involving various balancing measures when modelling severely imbalanced datasets. Additional explicit balancing measures other than those already apart of the Conformal Prediction framework are shown not to be required. The Aggregated Conformal Prediction procedure appears to be a promising approach for severely imbalanced datasets in order to retrieve a large majority of active minority class compounds while avoiding information loss or distortion. (C) 2017 Elsevier Inc. All rights reserved.
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