Abstract
Machine learning (ML) is a scientific technology related to data learning that can help machines learn patterns from existing complex data to predict future behavioral outcomes and trends. In this paper, we use 16 different ML algorithms and 5 different hyper-parameters optimal methods to model a circularly polarized omnidirectional base station antenna. The mean absolute error is 8.431, the root mean squared error is 11.100, the coefficient of determination is 0.967, and the adjusted coefficient of determination is 0.944, which means evaluation metrics are excellent.
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.