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For: Perales-González C, Carbonero-Ruz M, Becerra-Alonso D, Pérez-Rodríguez J, Fernández-Navarro F. Regularized ensemble neural networks models in the Extreme Learning Machine framework. Neurocomputing 2019. [DOI: 10.1016/j.neucom.2019.06.040] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Number Cited by Other Article(s)
1
A multi-class classification model with parametrized target outputs for randomized-based feedforward neural networks. Appl Soft Comput 2022. [DOI: 10.1016/j.asoc.2022.109914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
2
Pasha SJ, Mohamed ES. Advanced hybrid ensemble gain ratio feature selection model using machine learning for enhanced disease risk prediction. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.101064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]  Open
3
Preeti, Bala R, Dagar A, Singh RP. A novel online sequential extreme learning machine with L2,1-norm regularization for prediction problems. APPL INTELL 2020. [DOI: 10.1007/s10489-020-01890-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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