[ENH] CMI estimators using forests

[adam2392]

Supersedes: #94

Changes proposed in this pull request:

• implements KSG estimator using scipy KDTree
• implements KSG estimator using an unsupervised tree, which is validated on a Jupyter notebook

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[codecov]

Codecov Report

Attention: 402 lines in your changes are missing coverage. Please review.

Comparison is base (386578a) 88.86% compared to head (64ddf97) 76.43%.

❗ Current head 64ddf97 differs from pull request most recent head dd4409f. Consider uploading reports for the commit dd4409f to get more accurate results

Additional details and impacted files

@@             Coverage Diff             @@
##             main     #110       +/-   ##
===========================================
- Coverage   88.86%   76.43%   -12.43%     
===========================================
  Files          41       32        -9     
  Lines        3439     2521      -918     
===========================================
- Hits         3056     1927     -1129     
- Misses        383      594      +211     

Files	Coverage Δ
sktree/experimental/__init__.py	100.00% <100.00%> (ø)
sktree/experimental/tests/test_monte_carlo.py	100.00% <100.00%> (ø)
sktree/utils.py	25.00% <25.00%> (ø)
sktree/experimental/tests/test_ksg.py	60.00% <60.00%> (ø)
sktree/experimental/mutual_info.py	33.33% <10.52%> (+12.82%)	⬆️
sktree/experimental/monte_carlo.py	69.11% <69.11%> (ø)
sktree/neighbors.py	58.58% <45.90%> (-27.63%)	⬇️
sktree/experimental/simulate.py	41.25% <8.33%> (-46.88%)	⬇️
sktree/experimental/forest.py	15.38% <15.38%> (ø)
sktree/experimental/ksg.py	17.12% <17.12%> (ø)

... and 29 files with indirect coverage changes

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