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@naresh-bachwani naresh-bachwani commented Aug 22, 2019

This PR fixes #316. I added the following features :

  1. Added a parameter for showing cumulative explained variance.
  2. Added a parameter which takes percentage of variance needed in the components and shows corresponding principal components.

Sample Code and Plot

from yellowbrick.features.decomposition import ExplainedVariance

from sklearn.datasets import load_digits
digits = load_digits()
X = digits.data

viz = ExplainedVariance(cumulative=True, cutoff=85)
viz.fit(X)
viz.transform(X)
viz.poof("Varaince.png")

abc

Still to do:

  • Add more features.
  • Add tests.
  • Add documentation

More Todos:

  • Is the commit message formatted correctly?
  • Have you noted the new functionality/bugfix in the release notes of the next release?
  • Included a sample plot to visually illustrate your changes?
  • Do all of your functions and methods have docstrings?
  • Have you added/updated unit tests where appropriate?
  • Have you updated the baseline images if necessary?
  • Have you run the unit tests using pytest?
  • Is your code style correct (are you using PEP8, pyflakes)?
  • Have you documented your new feature/functionality in the docs?
  • Have you built the docs using make html?

@naresh-bachwani naresh-bachwani changed the title Added features to Decomposition.py [WIP] Added features to Decomposition.py Aug 22, 2019
@bbengfort bbengfort mentioned this pull request Feb 11, 2020
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@bbengfort
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@naresh-bachwani I've merged these changes into #1037 so that we can incoporate them into v1.1 -- thank you so much!

@bbengfort bbengfort closed this Feb 12, 2020
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Finish decomposition explained variance visualizer

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