Contents

yellowbrick 1.5

0

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

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

Stars: 3745, Watchers: 3745, Forks: 528, Open Issues: 85

The DistrictDataLabs/yellowbrick repo was created 6 years ago and was last updated 2 days ago.
The project is very popular with an impressive 3745 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/
GitHub Repo
https://github.com/DistrictDataLabs/yellowbrick

Classifiers

  • Scientific/Engineering/Visualization
  • Software Development
  • Software Development/Libraries/Python Modules
No  yellowbrick  pypi packages just yet.

Errors

A list of common yellowbrick errors.

Code Examples

Here are some yellowbrick code examples and snippets.

GitHub Issues

The yellowbrick package has 85 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

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