| Autor: |
Bukauskas, M., Mantas Lukoševičius |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Scopus-Elsevier |
| Popis: |
Machine learning is constantly gaining popularity in real life applications. And one of them is prediction of various real-life events that depend on a huge number of factors that are hard to evaluate. In this article we describe the process of applying XGBoost — one of supervised machine learning methods — to help in prediction and localization of accidents in the district heating network of Kaunas region. We also investigate the importance of the different factors for these events. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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