[DOC] Add Quantile forest examples

[SUKI-O]

Fixes #87

Changes proposed in this pull request:

• Add examples to show how to use RandomForestRegressor class to genera quantile predictions.

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[adam2392]

The 4 rendered artifacts: https://output.circle-artifacts.com/output/job/5db6e8d1-7cbe-4795-80d5-bbe5ab46dde6/artifacts/0/dev/use.html

@SUKI-O perhaps we can put this into its own section? I.e. Quantile Predictions? See the other example sections. This will help group the examples better.

[adam2392]

Great start and very encouraging that the simulations look very similar to those in quantile-forests.

Can you try to break up each example to make them easier to read?

For example, see the following example: https://output.circle-artifacts.com/output/job/5db6e8d1-7cbe-4795-80d5-bbe5ab46dde6/artifacts/0/dev/auto_examples/outlier_detection/plot_extended_isolation_forest.html#sphx-glr-auto-examples-outlier-detection-plot-extended-isolation-forest-py

In addition, perhaps we can be more explicit about what each example should show. What is the take-away message? E.g. in the right-skewed simulation, is it that QORF is better than standard ORF? What does better mean?

[sampan501]

Looks good after removing the print statements that @adam2392 referenced

[adam2392]

https://output.circle-artifacts.com/output/job/eb2e193e-9f05-4d58-903b-41b9a7cf478c/artifacts/0/dev/use.html

I don't see the examples rendered now so there's probably an error in your change. You can leverage the development guide to build the docs locally for yourself to peruse.

[adam2392]

You are probably missing a section header which is rendered from the README files inside each subsection

[adam2392]

I know the examples are copied "as-is" from quantile-forests, but I think their documentation is not as comprehensive as I would've liked.

The examples could use a bit more explanation. Otherwise, someone reading these have no idea how to interpret the results, or the figures. WDYT @SUKI-O @sampan501 @PSSF23 ?

[sampan501]

I think the only thing missing is a few comments about what exactly you are plotting and how to interpret the plots and we should be good to go

[adam2392]

Few minor changes and then LGTM.

Generally, it's useful to render the docs locally to see if there's any formatting issues.

Xref: https://output.circle-artifacts.com/output/job/b7f1c854-cb46-4c2d-8a79-57965fe88bd9/artifacts/0/dev/use.html#quantile-predictions-with-random-forest