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Using Model Trees and Their Ensembles for Imbalanced Data.

, , , and . CAEPIA, volume 7023 of Lecture Notes in Computer Science, page 94-103. Springer, (2011)

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Ensembles of Decision Trees for Imbalanced Data., , and . MCS, volume 6713 of Lecture Notes in Computer Science, page 76-85. Springer, (2011)An Experimental Study on Ensembles of Functional Trees., , , and . MCS, volume 5997 of Lecture Notes in Computer Science, page 64-73. Springer, (2010)Imbalanced Learning Ensembles for Defect Detection in X-Ray Images., , , and . IEA/AIE, volume 7906 of Lecture Notes in Computer Science, page 654-663. Springer, (2013)An Innovative Moodle Final Project Management Module for Bachelor and Master's Studies., , , and . Rev. Iberoam. de Tecnol. del Aprendiz., 8 (3): 103-110 (2013)Instance selection for regression: Adapting DROP., , , and . Neurocomputing, (2016)Instance selection improves geometric mean accuracy: a study on imbalanced data classification., , , and . Prog. Artif. Intell., 8 (2): 215-228 (2019)Rotation Forests for regression., , , and . Appl. Math. Comput., 219 (19): 9914-9924 (2013)Using Model Trees and Their Ensembles for Imbalanced Data., , , and . CAEPIA, volume 7023 of Lecture Notes in Computer Science, page 94-103. Springer, (2011)Addressing data scarcity in protein fitness landscape analysis: A study on semi-supervised and deep transfer learning techniques., , , , and . Inf. Fusion, (February 2024)An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees., , , and . MCS, volume 9132 of Lecture Notes in Computer Science, page 181-193. Springer, (2015)