8000 DOC proposal: visualizing cross-validation iterators · Issue #11362 · scikit-learn/scikit-learn · GitHub
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choldgraf opened this issue Jun 26, 2018 · 6 comments · Fixed by #11475
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DOC proposal: visualizing cross-validation iterators #11362

choldgraf opened this issue Jun 26, 2018 · 6 comments · Fixed by #11475

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@choldgraf
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choldgraf commented Jun 26, 2018 •
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Description

One of the visualizations I find most intriguing for scikit-learn is the visualization of predictions on a classification problem for many classifiers. This one:

I have something similar that I use to demonstrate how different cross-validation objects work. It has a similar style to it, and is done with very few lines of code. It makes plots like:

image

and

image

Would an example like this that loops through several cross-validation objects be helpful? I find it much easier to teach what each CV object does using visual plots like this rather than printing out the indices.

Just checking if folks would be interested in this before I make a PR :-)
@jnothman
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jnothman commented Jun 26, 2018 via email

@agramfort
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agramfort commented Jun 27, 2018 via email

@TomDLT
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TomDLT commented Jun 28, 2018

+1
Though I don't understand the link with the classification example, which does not demonstrate cross-validation but classification.

@amueller
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amueller commented Jun 28, 2018 •
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I have several scripts that do something like that.

Feel free to have a look at / steal from here:
https://github.com/amueller/introduction_to_ml_with_python/blob/master/mglearn/plot_cross_validation.py

and here:
https://github.com/amueller/introduction_to_ml_with_python/blob/master/05-model-evaluation-and-improvement.ipynb

@choldgraf
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@amueller oooh those look quite nice, I'll give em a shot

@amueller
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They are not unified right now, there's different functions for different cross-validation iterators. I think they can be generalized though.

@choldgraf choldgraf mentioned this issue Jul 10, 2018
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[MRG+1] EXA Adding cv indices example choldgraf/scikit-learn
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@jnothman @agramfort @amueller @choldgraf @TomDLT
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