FIX: Fix html widget docs links

[david-cortes-intel]

Description

Add a comprehensive description of proposed changes

List associated issue number(s) if exist(s): #6 (for example)

Documentation PR (if needed): #1340 (for example)

Benchmarks PR (if needed): IntelPython/scikit-learn_bench#155 (for example)

---

This PR fixes an issue in which the HTML widget representations of sklearnex were not showing the usual help button that base sklearn estimators have.

Since the classes have the exact same arguments and docs as those of sklearn, the logic in this PR is to make them point to the docs from sklearn.

Before:

After:

Checklist to comply with before moving PR from draft:

PR completeness and readability

• I have reviewed my changes thoroughly before submitting this pull request.
• I have commented my code, particularly in hard-to-understand areas.
• Git commit message contains an appropriate signed-off-by string (see CONTRIBUTING.md for details).
• I have added a respective label(s) to PR if I have a permission for that.
• I have resolved any merge conflicts that might occur with the base branch.

Testing

• I have run it locally and tested the changes extensively.
• All CI jobs are green or I have provided justification why they aren't.

Performance

Not applicable.

[david-cortes-intel]

/intelci: run

[codecov]

Codecov Report

Attention: Patch coverage is 95.55556% with 2 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
sklearnex/_utils.py	91.30%	1 Missing and 1 partial ⚠️

Flag	Coverage Δ
azure	78.00% <93.33%> (?)
github	71.03% <88.88%> (+0.02%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines	Coverage Δ
sklearnex/cluster/dbscan.py	92.10% <100.00%> (+3.94%)	⬆️
sklearnex/cluster/k_means.py	89.93% <100.00%> (+6.04%)	⬆️
sklearnex/decomposition/pca.py	89.63% <100.00%> (+16.19%)	⬆️
sklearnex/ensemble/_forest.py	70.09% <100.00%> (+13.12%)	⬆️
sklearnex/linear_model/linear.py	83.78% <100.00%> (+4.05%)	⬆️
sklearnex/linear_model/logistic_regression.py	54.67% <100.00%> (+1.43%)	⬆️
sklearnex/linear_model/ridge.py	79.86% <100.00%> (+6.04%)	⬆️
sklearnex/manifold/t_sne.py	100.00% <100.00%> (ø)
sklearnex/neighbors/common.py	91.81% <100.00%> (ø)
sklearnex/svm/_common.py	77.59% <100.00%> (+2.18%)	⬆️
... and 1 more

... and 45 files with indirect coverage changes

[david-cortes-intel]

/intelci: run