FIX: Fix processing of sparse data frames

[david-cortes-intel]

Description

Many estimators check for sparse inputs using scipy's issparse, but sklearn's data validators also take sparse data frames as sparse and convert them to COO/CSC/CSR internally, whereas sklearnex assumes that data frames are always dense.

This PR fixes the sparsity checks to consider also sparse data frames, and adds tests along the way to ensure that they are processed in the right format.

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Checklist:

Completeness and readability

• 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 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.
• I have extended testing suite if new functionality was introduced in this PR.

[david-cortes-intel]

/intelci: run

[david-cortes-intel]

/intelci: run