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Graph-Based Approaches for Over-Sampling in the Context of Ordinal Regression.

, , , and . IEEE Trans. Knowl. Data Eng., 27 (5): 1233-1245 (2015)

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Negative Correlation Ensemble Learning for Ordinal Regression., , , and . IEEE Trans. Neural Networks Learn. Syst., 24 (11): 1836-1849 (2013)Evolutionary Ordinal Extreme Learning Machine., , and . HAIS, volume 8073 of Lecture Notes in Computer Science, page 500-509. Springer, (2013)Time series forecasting by recurrent product unit neural networks., , , , and . Neural Comput. Appl., 29 (3): 779-791 (2018)Cumulative link models for deep ordinal classification., , and . Neurocomputing, (2020)Optimising Convolutional Neural Networks using a Hybrid Statistically-driven Coral Reef Optimisation algorithm., , , , and . Appl. Soft Comput., (2020)Exploitation of Pairwise Class Distances for Ordinal Classification., , , and . Neural Comput., 25 (9): 2450-2485 (2013)Addressing remitting behavior using an ordinal classification approach., , and . Expert Syst. Appl., 41 (10): 4752-4761 (2014)Identification of extreme wave heights with an evolutionary algorithm in combination with a likelihood-based segmentation., , , and . Progress in AI, 6 (1): 59-66 (2017)An Empirical Validation of a New Memetic CRO Algorithm for the Approximation of Time Series., , , and . CAEPIA, volume 11160 of Lecture Notes in Computer Science, page 209-218. Springer, (2018)Overcoming the Linearity of Ordinal Logistic Regression Adding Non-linear Covariates from Evolutionary Hybrid Neural Network Models., , , and . CAEPIA, volume 9422 of Lecture Notes in Computer Science, page 301-311. Springer, (2015)