[DEM-362] Updates for Bayer Canola workflow

[marissakivi]

Updates for Bayer Canola workflow

What?

• Updated seaborn version to ensure compatibility with other libraries (dependency resolution was failing)
• Added "classification" model capability to lasso_feature_selection(). This is currently using LinearSVC() with an L1 penalty instead of Lasso() to penalize features and, thereby, perform feature selection. Another option would be LogisticRegression() with an L1 penalty.
• Some small adjustments to existing functions in utils.py to make ML workflow sleeker and allow for customized figures.

Why?

• Fulfill on Bayer Canola Phase I

CR Checklist

• Read through code changes. Any issues that you can see? Do the code changes make sense?

PR Checklist

• Merged latest main
• Updated version number
• Version numbers match between package _version.py and pyproject.toml
• Ran poetry update and committed pyproject.toml and poetry.lock
• Ran poetry run pre-commit autoupdate

Breaking Changes

[marissakivi]

Aside from some minor changes that enable us to do "classification" feature selection with the same module, the other major change to note in this file is a move to using a config parameter which stores all of the data and config information for the different feature selection parts. This helps to clean things up a bit and to ensure that we aren't passing an incorrect value within one of the many function calls.

[marissakivi]

I added the scatter_kws argument to this function which helps us to customize the point attributes within a 1-to-1 plot.

[tnigon]

Besides the one minor question, everything looks good to me!