Update to PR Curve docs

[rebeccabilbro]

This PR closes #602 and closes #1049, which called on us to flesh out and clarify the interpretation and usage of the PrecisionRecallCurve visualizer.

I have made the following changes:

1. Added explanatory text to the docstrings of the visualizer and its quick method per Better Documentation for Precision-Recall Curves #602
2. Fleshed out the docs with examples and use cases per Better Documentation for Precision-Recall Curves #602
3. Updated the definition of "precision" given the discussion in Definition of “Precision” seems incorrect... #1049

Sample Code and Plot

Added model comparison examples to the docs, e.g.:

CHECKLIST

• 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?

[bbengfort]

Thank you for taking this on!

[bbengfort]

Also, sorry about the confusion, I didn't see @Kautumn06 was asked to review - so I took myself off of the review.

[rebeccabilbro]

Thank you @bbengfort!
@Kautumn06 — when you're ready, I'd sure appreciate your careful inspection of the new documentation around PR curves. I already found a few typos 😊 and I'm sure you'll find more!

[bbengfort]

This is a very comprehensive update of all of the locations we describe precision and recall. I really appreciate the thought and care you put into this!

Note that I'm taking this PR review so that @Kautumn06 can focus on #1078