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Yellowbrick is a suite of visual analysis and diagnostic tools designed to facilitate machine learning with Scikit-Learn. The package includes visualizations that can help users navigate the feature selection process, build intuition around model selection, diagnose common problems like bias, heteroscedasticity, underfit, and overtraining, and support hyperparameter tuning to steer predictive models toward more successful results.

Some of the available tools include:

  • histograms

  • scatter plot matrices

  • parallel coordinates

  • jointplots

  • ROC curves

  • classification heatmaps

  • residual plots

  • validation curves

  • gridsearch heatmaps

For more, please see the full documentation at: http://yellowbrick.readthedocs.org/en/latest/

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Release files for yellowbrick 0.3.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for yellowbrick 0.3.2
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yellowbrick-0.3.2.tar.gz 9.3 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for yellowbrick 0.3.2
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yellowbrick-0.3.2-py2.py3-none-any.whl Python 3, Python 2 none any Details

Total release size: 9.4 MB

Release files / yellowbrick-0.3.2.tar.gz

Download URL yellowbrick-0.3.2.tar.gz
Size 9.3 MB
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Release files / yellowbrick-0.3.2-py2.py3-none-any.whl

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Size 55.5 kB
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1.5

2 release files

1.4

2 release files

1.3

2 release files

1.2.1

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1.2

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1.1

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1.0.1

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1.0

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0.9.1

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0.9

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0.8

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0.7

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0.6

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0.5

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0.4.2

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0.4.1

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0.4

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0.3.3

2 release files

This release

0.3.2 This release

2 release files

0.3.1

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0.1

2 release files

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