Chapter Supporting decision-makers in healthcare domain. A comparative study of two interpretative proposals for Random Forests
The growing success of Machine Learning (ML) is making significant improvements to predictive models, facilitating their integration in various application fields, especially the healthcare context. However, it still has limitations and drawbacks, such as the lack of interpretability which does not...
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| Diğer Yazarlar: | , |
| Materyal Türü: | Elektronik Kitap Bölümü |
| Dil: | İngilizce |
| Baskı/Yayın Bilgisi: |
Florence
Firenze University Press
2021
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| Seri Bilgileri: | Proceedings e report
132 |
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| Online Erişim: | OAPEN Library: download the publication OAPEN Library: description of the publication |
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DOAB: description of the publication
Chapter Supporting decision-makers in healthcare domain. A comparative study of two interpretative proposals for Random Forests
Baskı/Yayın Bilgisi 2021
DOAB: download the publication
DOAB: description of the publication
Elektronik
Kitap Bölümü
Search Result 2
Search Result 3
DOAB: description of the publication
Chapter Supporting decision-makers in healthcare domain. A comparative study of two interpretative proposals for Random Forests
Baskı/Yayın Bilgisi 2021
DOAB: download the publication
DOAB: description of the publication
Elektronik
Kitap Bölümü