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Smart city article details
| Title | Modelling 5G Data Using Tree-Based Machine Learning Models |
|---|---|
| ID_Doc | 37645 |
| Authors | Mithillesh Kumar P.; Supriya M. |
| Year | 2023 |
| Published | Lecture Notes in Networks and Systems, 473 |
| DOI | http://dx.doi.org/10.1007/978-981-19-2821-5_7 |
| Abstract | 5G or fifth generation is the latest in the communication technology which is being researched worldwide as a successor to the current 4G technology. 5G operates on higher bandwidth with higher data rates of the order of Gbit/s. 5G is estimated to play a major role in the development of smart cities and IoT use cases. Lumos 5G is one of the groups researching on the topic. In this paper, the throughput obtained under various conditions is analysed as a regression model in machine learning with the features as continuous variables. It is observed that the newer tree machine learning models are performing better on the dataset than the traditional tree models. This is verified by performing a tenfold cross-validation check on the best performing models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. |
| Author Keywords | 5G; Cross-validation; Regression; Throughput; Trees |
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