Statistics

These examples take quite a long time to run, and they make our documentation CI fail quite frequently due to timeout. It'd be nice to speed the up a little bit.

To contributors: if you want to work on an example, first have a look at the example, and if you think you're comfortable working on it and have found a potential way to speed-up execution time while preserving the educational message

Collection of follow-ups to #5827. These can/should be broken out into individual PRs. Many are relatively straightforward and would make a good first PR.

General

• Documentation (none was added in original PR).
• Release notes.
• Example notebook.
• Double-check how sm.tsa.arima.ARIMA works with fix_params (it should fail except when the fit method is statespace

The source link in page geometric_mean_score is
https://github.com/scikit-learn-contrib/imbalanced-learn/blob/dfc44e2/imblearn/utils/_validation.py#L492

However, it should be
https://github.com/scikit-learn-contrib/imbalanced-learn/blob/f1abf75/i

See:
gonum/gonum#845 (comment)

Are there any plans to add a Zero-Inflated Poisson (ZIP) and Zero-Inflated Negative Binomial (ZINB) to TFP? Those are usually very common distributions in other packages, and it shouldn't be hard to implement.

Since the default output is meant to be human-readable, would it make sense to add thousands separators to make the output more easily readable?