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A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests.

, , and . Expert Syst. Appl., 36 (4): 7798-7808 (2009)

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A First Study on Decomposition Strategies with Data with Class Noise Using Decision Trees., , , and . HAIS (2), volume 7209 of Lecture Notes in Computer Science, page 25-35. Springer, (2012)SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering., , , and . Inf. Sci., (2015)Towards highly accurate coral texture images classification using deep convolutional neural networks and data augmentation., , , , , and . Expert Syst. Appl., (2019)A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost., , and . HAIS, volume 10334 of Lecture Notes in Computer Science, page 268-280. Springer, (2017)Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure., , and . Neurocomputing, (2016)Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness., , , and . Inf. Sci., (2013)Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data., , , , , and . WIREs Data Mining Knowl. Discov., (2019)KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework., , , , and . J. Multiple Valued Log. Soft Comput., 17 (2-3): 255-287 (2011)Synthetic Sample Generation for Label Distribution Learning., , , and . Inf. Sci., (2021)Multiple instance classification: Bag noise filtering for negative instance noise cleaning., , , and . Inf. Sci., (2021)