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Dissimilarity-Based Learning from Imbalanced Data with Small Disjuncts and Noise.

, , , and . IbPRIA, volume 9117 of Lecture Notes in Computer Science, page 370-378. Springer, (2015)

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Use of Ensemble Based on GA for Imbalance Problem., , , and . ISNN (2), volume 5552 of Lecture Notes in Computer Science, page 547-554. Springer, (2009)Cost-Sensitive Neural Networks and Editing Techniques for Imbalance Problems., , , and . MCPR, volume 6256 of Lecture Notes in Computer Science, page 180-188. Springer, (2010)A New Performance Evaluation Method for Two-Class Imbalanced Problems., , and . SSPR/SPR, volume 5342 of Lecture Notes in Computer Science, page 917-925. Springer, (2008)On the effectiveness of preprocessing methods when dealing with different levels of class imbalance., , and . Knowl. Based Syst., 25 (1): 13-21 (2012)Strategies for learning in class imbalance problems., , , and . Pattern Recognit., 36 (3): 849-851 (2003)Implementing a Novel Use of Multicriteria Decision Analysis to Select IIoT Platforms for Smart Manufacturing., , , , and . Symmetry, 12 (3): 368 (2020)Assessment of Financial Risk Prediction Models with Multi-criteria Decision Making Methods., , and . ICONIP (2), volume 7664 of Lecture Notes in Computer Science, page 60-67. Springer, (2012)Understanding the apparent superiority of over-sampling through an analysis of local information for class-imbalanced data., , , , and . Expert Syst. Appl., (2020)Addressing the Links Between Dimensionality and Data Characteristics in Gene-Expression Microarrays., and . LOPAL, page 1:1-1:6. ACM, (2018)Associative learning on imbalanced environments: An empirical study., , , and . Expert Syst. Appl., (2016)