[ENH] Optimize Unsuprf

[adam2392]

Towards: #113

Changes proposed in this pull request:

• Changes fastBIC to "fasterBIC" framework

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[codecov]

Codecov Report

Patch coverage: 98.36% and project coverage change: +0.21% 🎉

Comparison is base (3b124e3) 86.52% compared to head (9b4ff1b) 86.73%.
Report is 1 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #114      +/-   ##
==========================================
+ Coverage   86.52%   86.73%   +0.21%     
==========================================
  Files          26       26              
  Lines        2063     2111      +48     
==========================================
+ Hits         1785     1831      +46     
- Misses        278      280       +2     

Files Changed	Coverage Δ
sktree/ensemble/_unsupervised_forest.py	70.63% <ø> (ø)
sktree/tree/_honest_tree.py	99.40% <97.67%> (-0.60%)	⬇️
sktree/ensemble/_honest_forest.py	91.46% <100.00%> (ø)
sktree/tests/test_supervised_forest.py	99.41% <100.00%> (+<0.01%)	⬆️
sktree/tree/_classes.py	75.00% <100.00%> (+0.06%)	⬆️
sktree/tree/tests/test_unsupervised_tree.py	100.00% <100.00%> (ø)

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[adam2392]

@PSSF23 can you add the support to honest tree and forest for partial fit to fix the CI here?

=========================== short test summary info ============================
FAILED sktree/tests/test_honest_forest.py::test_sklearn_compatible_estimator[HonestForestClassifier(n_estimators=10,random_state=0)-check_fit_score_takes_y] - AttributeError: 'HonestTreeClassifier' object has no attribute 'partial_fit'
FAILED sktree/tests/test_honest_forest.py::test_sklearn_compatible_estimator[HonestForestClassifier(n_estimators=10,random_state=0)-check_estimators_partial_fit_n_features] - TypeError: fit() got an unexpected keyword argument 'classes'

Feel free to commit directly to the branch once you have something working locally? Afterwards, I can merge this PR and the forests/trees in scikit-tree should have partial_fit enabled.

[PSSF23]

@adam2392 I have optimized the honest fitting as we currently have classes as a variable. Right now only the samples used for tree structures are included in the fitting, instead of the current sample_weight=0 method.

[PSSF23]

black version 22.12.0 is affecting the linting checks. Should we update it?

[adam2392]

There are some errors in the implementation. Also do you mind adding the functionality to the forest as well?

I'm not as sure what needs to get added to partial_fit. As long as it passes the check_estimator unit-tests then it should be good on the CIs

[PSSF23]

I think all CIs work now.

[adam2392]

Cool thanks @PSSF23!