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Install this package:

emerge -a dev-python/dtreeviz

Package Information

Description:

A python library for decision tree visualization and model interpretation. Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. The visualizations are inspired by an educational animation by R2D3; A visual introduction to machine learning. Please see How to visualize decision trees for deeper discussion of our decision tree visualization library and the visual design decisions we made.

Homepage:

https://github.com/parrt/dtreeviz https://pypi.org/project/dtreeviz/

License:

MIT

Versions

Metadata

Description

• A python library for decision tree visualization and model interpretation. Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. The visualizations are inspired by an educational animation by R2D3; A visual introduction to machine learning. Please see How to visualize decision trees for deeper discussion of our decision tree visualization library and the visual design decisions we made.

Maintainers

• Tomas Fabrizio Orsi (torsi@fi.uba.ar) - Type: person

Upstream

• Remote IDs:
  • github: parrt/dtreeviz
  • pypi: dtreeviz

<pkgmetadata>
	<maintainer type="person">
		<email>torsi@fi.uba.ar</email>
		<name>Tomas Fabrizio Orsi</name>
	</maintainer>
	<longdescription>A python library for decision tree visualization and model interpretation. Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. The visualizations are inspired by an educational animation by R2D3; A visual introduction to machine learning. Please see How to visualize decision trees for deeper discussion of our decision tree visualization library and the visual design decisions we made.</longdescription>
	<upstream>
		<remote-id type="github">parrt/dtreeviz</remote-id>
		<remote-id type="pypi">dtreeviz</remote-id>
	</upstream>
</pkgmetadata>

Lint Warnings

• [Warning] Ebuild 2.2.2 has a line exceeding 80 positions on line 10.
• [Error] Manifest entry for unused DIST file 'dtreeviz-2.2.2.tar.gz'
• [Error] Repository is missing a repo-name in metadata/layout.conf or profiles/repo_name
• [Notice] Package has only unstable keywords for arch(es): [ amd64 ], all versions are unstable: [ 2.2.2 ]

Manifest