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Decision trees are a family of algorithms that are based around a tree-like structure of decision rules. These algorithms often perform well in tasks such as prediction and classification. This lesson explores the properties of tree models in the context of mortality prediction.
The dataset that we will be using for this project is a subset of the eICU Collaborative Research Database that has been created for demonstration purposes.
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Lesson Title
Introduction to Tree Models in Python
Lesson Repository URL
https://github.com/carpentries-incubator/machine-learning-trees-python
Lesson Website URL
https://carpentries-incubator.github.io/machine-learning-trees-python/
Lesson Description
Decision trees are a family of algorithms that are based around a tree-like structure of decision rules. These algorithms often perform well in tasks such as prediction and classification. This lesson explores the properties of tree models in the context of mortality prediction.
The dataset that we will be using for this project is a subset of the eICU Collaborative Research Database that has been created for demonstration purposes.
Author Usernames
@tompollard
Zenodo DOI
No response
Differences From Existing Lessons
No response
Confirmation of Lesson Requirements
JOSE Submission Requirements
paper.md
andpaper.bib
files as described in the JOSE submission guide for learning modulesPotential Reviewers
No response
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