Upgrade scikit-learn to v1.0.1

[desilinguist]

This PR closes #699.

This change is pretty straightforward but it’s definitely backwards incompatible which we will reflect in the release version when we put together the release.

The change specifically motivated by the upgrade are:

• Update requirements.txt and conda_requirements.txt to point to the latest scikit-learn (v1.0.1) and allow up to v1.0.2.
• Use squared_error as the default value of the loss parameter for RANSACRegressor.
• Use toarray() for converting sparse numpy arrays to dense instead of todense() since the latter returns an np.matrix instead of an np.ndarray. Scikit-learn is planning to drop support for np.matrix inputs and is already displaying FutureWarnings.
• Force normalize to False for Lars models
  • Scikit-learn v1.0 will be deprecating the normalize attribute for linear models
  • This attribute is set to False by default in most scikit-learn linear models anyway and so no warnings are surfaced in SKLL.
  • However, for Lars, the default value of normalize is still set to True and so we need to force it to False to avoid FutureWarning instances.
  • The if statement added will actually lead to an execption in the _create_estimator() method when the normalize attribute doesn't exist, so that will be the perfect reminder to excise it entirely when the time comes.

Other changes include:

• Update Python versions in CI builds (3.9 for Windows/Azure and 3.9 for Linux/Gitlab)
• Update pre-commit and pre-commit hooks to their latest versions

[codecov[bot]]

Codecov Report

Merging #702 (afad8de) into main (4ead823) will increase coverage by 0.03%. The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main     #702      +/-   ##
==========================================
+ Coverage   96.85%   96.89%   +0.03%     
==========================================
  Files          63       63              
  Lines        9098     9197      +99     
==========================================
+ Hits         8812     8911      +99     
  Misses        286      286              

Impacted Files	Coverage Δ
tests/test_preprocessing.py	100.00% <ø> (ø)
skll/data/writers.py	94.17% <100.00%> (+0.06%)	:arrow_up:
skll/learner/__init__.py	97.13% <100.00%> (+0.04%)	:arrow_up:
skll/learner/utils.py	94.62% <100.00%> (+0.03%)	:arrow_up:
tests/test_commandline_utils.py	99.66% <100.00%> (+<0.01%)	:arrow_up:
tests/test_featureset.py	99.78% <100.00%> (+<0.01%)	:arrow_up:
tests/test_regression.py	99.64% <100.00%> (+<0.01%)	:arrow_up:
tests/test_cv.py	100.00% <0.00%> (ø)
tests/test_output.py	100.00% <0.00%> (ø)
tests/test_classification.py	100.00% <0.00%> (ø)
... and 14 more

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[mulhod]

Should the scikit-learn version also be updated in the Conda recipe? It is currently >=0.24.1,<=0.24.2. Would this version include 1.0, e.g. >=1.0,<=1.0.1?

[desilinguist]

Should the scikit-learn version also be updated in the Conda recipe? It is currently >=0.24.1,<=0.24.2. Would this version include 1.0, e.g. >=1.0,<=1.0.1?

Good catch! I will modify it to be the same as the requirements files.