Abstract
In recent years, Extreme Learning Machine (ELM) has attracted extensive attention in various research fields. To improve the performance of ELM, we propose an Extreme Learning Machine Based on Double Kernel Risk-Sensitive Loss (DKRSLELM) method in this paper. The Kernel Risk-Sensitive Loss (KRSL) is integrated into the objective function of ELM. This is because KRSL not only can effectively reduce the influence of noise and outliers, but also can eliminate the redundant neurons of ELM. In the experiment, we conduct a classification experiment on cancer integration data-sets. The experimental results indicate that our method can effectively improve the classification performance of ELM.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.