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| Stacking Ensemble Technique for Classifying Breast Cancer |
| Hyunjin Kwon, Jinhyeok Park, Youngho Lee |
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Healthc Inform Res. 2019;25(4):283-288. Published online October 31, 2019 DOI: https://doi.org/10.4258/hir.2019.25.4.283 |
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Stacking Ensemble Technique for Classifying Breast Cancer Healthcare Informatics Research. 2019;25(4):283  Can–Evo–Ens: Classifier stacking based evolutionary ensemble system for prediction of human breast cancer using amino acid sequences Journal of Biomedical Informatics. 2015;54:256-269 F-test feature selection in Stacking ensemble model for breast cancer prediction Procedia Computer Science. 2020;171:1561-1570 Classifying Breast Cancer Molecular Subtypes using Deep Clustering Approach . 2019; Using Ensemble Learning Libraries Ensemble Learning for AI Developers. 2020;61-96 Classifying sarcopenia: using median value or cut-off values? Breast Cancer Research and Treatment. 2019;176(2):479-479 Detection of Breast Cancer in Mammograms through a New Features Technique Breast Cancer and Breast Reconstruction. 2020; A novel technique: ensemble hybrid 1NN model using stacking approach International Journal of Information Technology. 2018; Evaluation of a New Ensemble Learning Framework for Mass Classification in Mammograms Clinical Breast Cancer. 2018;18(3):e407-e420 Sentinel lymph node biopsy for breast cancer: Combined dye-isotope technique Breast Cancer. 2000;7(4):389-397 |
