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CatBoost for big data: an interdisciplinary review
Gradient Boosted Decision Trees (GBDT’s) are a powerful tool for classification and regression tasks in Big Data. Researchers should be familiar with the strengths and weaknesses of current implementations of GBDT’s in order to use them effectively and make successful contributions. CatBoost is a me...
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| Veröffentlicht in: | J Big Data |
|---|---|
| Hauptverfasser: | , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Springer International Publishing
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7610170/ https://ncbi.nlm.nih.gov/pubmed/33169094 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s40537-020-00369-8 |
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