v1.4.0: Upgrade requirements

• Change python minor version to 3.11
• Change build tool to hatch
• Update build source from setup.py to pyproject.toml
• Update github action versions
• Remove black from github actions linting as it wouldn't read from pyproject.toml
• Add call method to Stree to support sklearn ensembles requirements for base estimators
• Update tests
• Update readthedocs configuration

v1.3.2: Fixing minor issues

• Reformat test with new black version
• Add separate methods to return nodes/leaves/depth
• Black format issue
• Update benchmark.ipynb

Working nicely with scikit-learn v 1.4.2 and python 3.11.5

v1.3.1: update to sklearn 1.2

Update to sklearn 1.2

v1.3.0: predict_proba

Update doc and version 1.30 (#55)

* Add complete classes counts to node and tests

* Implement optimized predict and new predict_proba

* Add predict_proba test

* Add python 3.10 to CI

* Update version number and documentation

v1.2.4: Graphviz (#52)

* Add graphviz representation of the tree

* Complete graphviz test
Add comments to some tests

* Add optional title to tree graph

* Add fontcolor keyword to nodes of the tree

* Add color keyword to arrows of graph

* Update version file to 1.2.4

v1.2.3

Fix random seed not used in fs_mutual (mutual_info_classif from sklearn.feature_selection) that produced flaky tests in odte

v1.2.2

• Add iwss and true random (only one combination generated) feature selection

• Update docs and source comments

• Remove obsolete binder links

v1.2.1

Add feature selection to node splits: f-value, mutual information, cfs and fcbf

1.2: Update version info (#42)

* Update version info and update docs (#41)

1.1: Add docs config

Added the following features:

• libsvm linear kernel
• normalization in a per node basis
• feature selection based on mutual information w.r.t. the label
• feature selection based on f-values ranking
• implement one versus one strategy in multi class