yellowbrick 1.5

A suite of visual analysis and diagnostic tools for machine learning.

Stars: 4191, Watchers: 4191, Forks: 550, Open Issues: 94

The DistrictDataLabs/yellowbrick repo was created 7 years ago and the last code push was 8 months ago.
The project is very popular with an impressive 4191 github stars!

How to Install yellowbrick

You can install yellowbrick using pip

pip install yellowbrick

or add it to a project with poetry

poetry add yellowbrick

Package Details

Author

The scikit-yb developers

License

Apache 2

Homepage

http://scikit-yb.org/

PyPi:

https://pypi.org/project/yellowbrick/

Documentation:

http://scikit-yb.org/

GitHub Repo:

https://github.com/DistrictDataLabs/yellowbrick

Classifiers

• Scientific/Engineering/Visualization
• Software Development
• Software Development/Libraries/Python Modules

Related Packages

Errors

A list of common yellowbrick errors.

Code Examples

Here are some yellowbrick code examples and snippets.

GitHub Issues

The yellowbrick package has 94 open issues on GitHub

• Learning Curve Documentation
• BUG: Corrects legend issues other than R2 in PredictionError
• Diagnostic Plots for Linear Regression Analysis
• BUG: Adds missing X and Y axes labels in ClassificationReport
• Argument to PredictionError is overwritten
• BUG: Fixes axes limit for PredictionError plot #1193
• Random input feature dropping curve, model selection visualization [issue #1024]
• Gap Statistic and Davies-Bouldin Index
• Model selection curve for Random Input Dropout
• AttributeError: 'KMeans' object has no attribute 'k'
• PredictionError plot forces min/max limits on the graph that are unhelpful if you have lots of tiny errors
• PredictionError hard codes score legend to R2 even when other scoring functions are used

See more issues on GitHub