Estimator has too many undocumented attributes:

• test_fit_docstring_attributes[OrthogonalMatchingPursuit-OrthogonalMatchingPursuit]
• test_fit_docstring_attributes[Lasso-Lasso]
• test_fit_docstring_attributes[LarsCV-LarsCV]
• test_fit_docstring_attributes[Birch-Birch]

Screenshot

Description

Unnecessary scrollbar

Design input

Please remove them.

cc @yousoph

Background

Having many parameters with defaults makes static typing a lot harder when one of them changes the return type, as they require many* overloads.

There's still no broad agreement about whether or not to deprecate the inplace argument, so in the meanwhile, if we force default-arguments to be keyword-only, then we can at least set the correct return types for these methods witho

Summary

When import streamlit and supervisely_lib together in a project there occurs a TypeError.

Steps to reproduce

Code snippet:

import streamlit as st
import supervisely_lib as sly

If applicable, please provide the steps we should take to reproduce the bug:

1. run the code with streamlit run ...
2. see error/traceback when you open the streamlit page

Is your feature request related to a problem? Please describe.
When working with a big piece of text, I sometimes scroll down and copy some text into another tab. When switching back to the first tab, both the input and the output pane is back on top. So I don't know where I was working just now.

Describe the solution you'd like
After tab switching, scroll position should be remembere

To Reproduce

Configure a reconciliation service that returns URIs as IDs.

Hovering over reconciliation suggestions, automatically matched values and manually mapped values will fail to retrieve the preview information as ID contained in the callback is truncated.

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 official instructions say to use joblib for pickling PyOD models.

This fails for AutoEncoders, or any other TensorFlow-backed model as far as I can tell. The error is:

>>> dump(model, 'model.joblib')
...
TypeError: can't pickle _thread.RLock objects

Note that it's not sufficient to save the underlying Keras S