Contents

yellowbrick 1.4

0

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

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

Stars: 3580, Watchers: 3580, Forks: 519, Open Issues: 92

The DistrictDataLabs/yellowbrick repo was created 5 years ago and was last updated 10 hours ago.
The project is very popular with an impressive 3580 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 92 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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