Feature Selection Visualization #7
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invalid
unrelated to primary development path
level: intermediate
python coding expertise required
priority: medium
can wait until after next release
type: question
more information is required
How do we adapt radviz, parallel coords, splom, etc. so that our tool is better/more capable than seaborn or pandas.
One idea is to perform automatic feature analysis and show which features are most visually relevant to the models. In that case we would pull the relevant code from the libraries and adapt it to our use.
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