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Improving the Performance of the RBF Neural Networks Trained with Imbalanced Samples.

, , , , and . IWANN, volume 4507 of Lecture Notes in Computer Science, page 162-169. Springer, (2007)

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On the k-NN performance in a challenging scenario of imbalance and overlapping., , and . Pattern Anal. Appl., 11 (3-4): 269-280 (2008)Associative learning on imbalanced environments: An empirical study., , , and . Expert Syst. Appl., (2016)On the effectiveness of preprocessing methods when dealing with different levels of class imbalance., , and . Knowl. Based Syst., 25 (1): 13-21 (2012)Understanding the apparent superiority of over-sampling through an analysis of local information for class-imbalanced data., , , , and . Expert Syst. Appl., (2020)On the Suitability of Numerical Performance Measures for Class Imbalance Problems., , and . ICPRAM (1), page 310-313. SciTePress, (2012)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)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)Strategies for learning in class imbalance problems., , , and . Pattern Recognit., 36 (3): 849-851 (2003)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)Instance Selection for the Nearest Neighbor Classifier: Connecting the Performance to the Underlying Data Structure., , , and . IbPRIA (1), volume 11867 of Lecture Notes in Computer Science, page 249-256. Springer, (2019)