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Describe the issue linked to the documentation

https://raw.githubusercontent.com/scikit-learn/scikit-learn/main/doc/logos/README.md

cc: @thomasjpfan

Suggest a potential alternative/fix

Update link for logo 3 so it's this one:
https://github.com/scikit-learn/scikit-learn/blob/main/doc/logos/scikit-learn-logo-without-subtitle.svg

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

See:
gonum/gonum#845 (comment)

The currently implemented version of the horseshoe distribution is not the parameterization that most ML papers use. This limits the ease of use of this as, for example, a prior in a tfp.layers.KLDivergenceAddLoss or in tfp.layers.DenseReparameterization. The regularized horseshoe would also be useful as an implemented distribution.

The alternative parameterization is shown here:
https://www.

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?

When there are not enough results, we tell the user that the experiment just started, so come back later. When the experiment dates are set to a future time, this language doesn't fit very well. We should adjust the language to take this future state into account when figuring out the message.

<img width="875" alt="CleanShot 2022-04-10 at 21 23 22@2x" src="https://user-images.githubusercontent

For example, the data is (3.8,4.5,4.6,4.7,4.9)
while I'm using tech.tablesaw.aggregate.AggregateFunctions.percentile function, the 90th percentile is 4.9, however, if the percentile function supports linear interpolation, the 90th percentile should be 4.82, which is adopted by most other programming languages.