The following publications are possibly variants of this publication:
- One-Class Classification Decomposition for Imbalanced Classification of Breast Cancer Malignancy DataBartosz Krawczyk, Lukasz Jelen, Adam Krzyzak, Thomas Fevens. icaisc 2014: 539-550 [doi]
- Comparison of Pleomorphic and Structural Features Used for Breast Cancer Malignancy ClassificationLukasz Jelen, Adam Krzyzak, Thomas Fevens. ai 2008: 138-149 [doi]
- Oversampling Methods for Classification of Imbalanced Breast Cancer Malignancy DataBartosz Krawczyk, Lukasz Jelen, Adam Krzyzak, Thomas Fevens. iccvg 2012: 483-490 [doi]
- Evolutionary Undersampling for Classification with Imbalanced Datasets: Proposals and TaxonomySalvador GarcÃa, Francisco Herrera. ec, 17(3):275-306, 2009. [doi]
- Classification of Breast Cancer Malignancy Using Cytological Images of Fine Needle Aspiration BiopsiesLukasz Jelen, Thomas Fevens, Adam Krzyzak. amcs, 18(1):75-83, 2008. [doi]
- Influence of nuclei segmentation on breast cancer malignancy classificationLukasz Jelen, Thomas Fevens, Adam Krzyzak. micad 2009: 726014 [doi]
- A Hybrid Surrogate Model for Evolutionary Undersampling in Imbalanced ClassificationHoang Lam Le, Dario Landa Silva, Mikel Galar, Salvador García, Isaac Triguero. cec 2020: 1-8 [doi]
- Evolutionary undersampling for imbalanced big data classificationIsaac Triguero, Mikel Galar, S. Vluymans, C. Cornelis, Humberto Bustince, Francisco Herrera, Y. Saeys. cec 2015: 715-722 [doi]