Yellowbrick : Analyse visuelle et outils de diagnostic

Analyse visuelle et outils de diagnostic pour faciliter la sélection de modèles d’apprentissage automatique!


Yellowbrick extends the Scikit-Learn API to make model selection and hyperparameter tuning easier. Under the hood, it’s using Matplotlib.


Interested in contributing to Yellowbrick? Yellowbrick is a welcoming, inclusive project and we would love to have you. We follow the Python Software Foundation Code of Conduct.

No matter your level of technical skill, you can be helpful. We appreciate bug reports, user testing, feature requests, bug fixes, product enhancements, and documentation improvements.

Check out the Contributing guide!

If you’ve signed up to do user testing, head over to the User Testing Instructions.

Please consider joining the Google Groups Listserv listserve so you can respond to questions.

Thank you for your contributions!

Concepts & API


The primary goal of Yellowbrick is to create a sensical API similar to Scikit-Learn.

Visualizers are the core objects in Yellowbrick. They are similar to transformers in Scikit-Learn. Visualizers can wrap a model estimator - similar to how the « ModelCV » (e.g. RidgeCV, LassoCV) methods work.

Some of our most popular visualizers include:

Feature Visualization

Classification Visualization

Regression Visualization

Clustering Visualization

Model Selection Visualization

Target Visualization

  • Balanced Binning Reference: generate a histogram with vertical lines showing the recommended value point to bin the data into evenly distributed bins

  • Class Balance: see how the distribution of classes affects the model

  • Feature Correlation: display the correlation between features and dependent variables

Text Visualization

… and more! Visualizers are being added all the time. Check the examples (or even the develop branch). Feel free to contribute your ideas for new Visualizers!

Getting Help

Can’t get someting to work? Here are places you can find help.

  1. The docs (you’re here!).

  2. Stack Overflow. If you ask a question, please tag it with « yellowbrick ».

  3. The Yellowbrick Google Groups Listserv.

  4. You can also Tweet or direct message us on Twitter @scikit_yb.

Find a Bug?

Check if there’s already an open issue on the topic. If needed, file an issue.

Open Source

The Yellowbrick license is an open source Apache 2.0 license. Yellowbrick enjoys a very active developer community; please consider Contributing!

Yellowbrick is hosted on GitHub. The issues and pull requests are tracked there.

Table of Contents

Indices and tables