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Unsupervised Feature Selection Based on Spectral Clustering with Maximum Relevancy and Minimum Redundancy Approach., und . Int. J. Pattern Recognit. Artif. Intell., 35 (11): 2150031:1-2150031:22 (2021)A GPU-based accelerated ELM and deep-ELM training algorithms for traditional and deep neural networks classifiers., , und . Intell. Syst. Appl., (2022)CCFS: A cooperating coevolution technique for large scale feature selection on microarray datasets., , und . Comput. Biol. Chem., (2018)Interpretability-based fuzzy decision tree classifier a hybrid of the subtractive clustering and the multi-objective evolutionary algorithm., , , und . Soft Comput., 17 (9): 1673-1686 (2013)Feature selection based on regularization of sparsity based regression models by hesitant fuzzy correlation., , und . Appl. Soft Comput., (2020)Regularizing extreme learning machine by dual locally linear embedding manifold learning for training multi-label neural network classifiers., , und . Eng. Appl. Artif. Intell., (2021)Supervised feature selection by constituting a basis for the original space of features and matrix factorization., , und . Int. J. Mach. Learn. Cybern., 11 (7): 1405-1421 (2020)DINO-CXR: A Self Supervised Method Based on Vision Transformer for Chest X-Ray Classification., , und . ISVC (2), Volume 14362 von Lecture Notes in Computer Science, Seite 320-331. Springer, (2023)A Definition for Hesitant fuzzy Partitions., , , und . Int. J. Comput. Intell. Syst., 9 (3): 497-505 (2016)Low-Redundant Unsupervised Feature Selection based on Data Structure Learning and Feature Orthogonalization., , , , und . Expert Syst. Appl., (2024)