Mlxtend

What's Changed
* Improved `plot_splits` for time series splits by d-kleine in https://github.com/rasbt/mlxtend/pull/1113
* Updated `publish` CI/CD workflow by d-kleine in https://github.com/rasbt/mlxtend/pull/1111
* Update exhaustive_feature_selector.py by Haider010 in https://github.com/rasbt/mlxtend/pull/1104
* fix: Code examples for the association_rules method have an execution… by MarceloNunesAlves in https://github.com/rasbt/mlxtend/pull/1115
* V0.23.3 by rasbt in https://github.com/rasbt/mlxtend/pull/1116

New Contributors
* Haider010 made their first contribution in https://github.com/rasbt/mlxtend/pull/1104
* MarceloNunesAlves made their first contribution in https://github.com/rasbt/mlxtend/pull/1115

**Full Changelog**: https://github.com/rasbt/mlxtend/compare/v0.23.2...v0.23.3

What's Changed
* Don't include tests in built wheel by carlsmedstad in https://github.com/rasbt/mlxtend/pull/1076
* Fix typo in OneRClassifier notebook by danickblouin in https://github.com/rasbt/mlxtend/pull/1084
* Update CI by rasbt in https://github.com/rasbt/mlxtend/pull/1089
* Most recent scikit-learn results in several failed unit tests by it176131 in https://github.com/rasbt/mlxtend/pull/1091
* Integrate scikit-learn's `set_output` method into `TransactionEncoder` by it176131 in https://github.com/rasbt/mlxtend/pull/1087
* Refactor bias_variance_decomposition test. by fkdosilovic in https://github.com/rasbt/mlxtend/pull/1081
* Update minor typos in fpgrowth.ipynb by tanmaychimurkar in https://github.com/rasbt/mlxtend/pull/1057
* Use scipy's decompositions in PCA. by fkdosilovic in https://github.com/rasbt/mlxtend/pull/1080
* Add Jaccard, Certainty, and Kulczynski association rules metrics by UltraArceus3 in https://github.com/rasbt/mlxtend/pull/1099
* FPGrowth/FPMax and Association Rules with the existence of missing values (1004) by zazass8 in https://github.com/rasbt/mlxtend/pull/1106
* SFS finalize_fit() support for numpy >= 2.0 by d-kleine in https://github.com/rasbt/mlxtend/pull/1107
* Fixed `_calc_score` for *scikit-learn* version compatibility by d-kleine in https://github.com/rasbt/mlxtend/pull/1109
* updated CI/CD workflows by d-kleine in https://github.com/rasbt/mlxtend/pull/1108
* Add PyPI deploy workflow by rasbt in https://github.com/rasbt/mlxtend/pull/1110

New Contributors
* carlsmedstad made their first contribution in https://github.com/rasbt/mlxtend/pull/1076
* danickblouin made their first contribution in https://github.com/rasbt/mlxtend/pull/1084
* it176131 made their first contribution in https://github.com/rasbt/mlxtend/pull/1091
* fkdosilovic made their first contribution in https://github.com/rasbt/mlxtend/pull/1081
* tanmaychimurkar made their first contribution in https://github.com/rasbt/mlxtend/pull/1057
* UltraArceus3 made their first contribution in https://github.com/rasbt/mlxtend/pull/1099
* zazass8 made their first contribution in https://github.com/rasbt/mlxtend/pull/1106
* d-kleine made their first contribution in https://github.com/rasbt/mlxtend/pull/1107

**Full Changelog**: https://github.com/rasbt/mlxtend/compare/v0.23.1...v0.23.2

Changes

- Updated dependency on distutils for python 3.12 and above ([[1072](https://github.com/rasbt/mlxtend/issues/1072)](https://github.com/rasbt/mlxtend/issues/1072) via [[peanutsee](https://github.com/peanutsee)](https://github.com/peanutsee))

Downloads

- [[Source code (zip)](https://github.com/rasbt/mlxtend/archive/v0.21.1.zip)](https://github.com/rasbt/mlxtend/archive/v0.21.1.zip)

- [[Source code (tar.gz)](https://github.com/rasbt/mlxtend/archive/v0.22.1.tar.gz)](https://github.com/rasbt/mlxtend/archive/v0.22.1.tar.gz)

Changes

- Address NumPy deprecations to make mlxtend compatible to NumPy 1.24
- Changed the signature of the `LinearRegression` model of sklearn in the test removing the `normalize` parameter as it is deprecated. ([[1036](https://github.com/rasbt/mlxtend/issues/1036)](https://github.com/rasbt/mlxtend/issues/1036))
- Add `pyproject.toml` to support PEP 518 builds ([[1065](https://github.com/rasbt/mlxtend/issues/1065)](https://github.com/rasbt/mlxtend/issues/1065) via [[jmahlik](https://github.com/jmahlik)](https://github.com/jmahlik))
- Fixed installation from sdist failing ([[1065](https://github.com/rasbt/mlxtend/issues/1065)](https://github.com/rasbt/mlxtend/issues/1065) via [[jmahlik](https://github.com/jmahlik)](https://github.com/jmahlik))
- Converted configuration to `pyproject.toml` ([[1065](https://github.com/rasbt/mlxtend/issues/1065)](https://github.com/rasbt/mlxtend/issues/1065) via [[jmahlik](https://github.com/jmahlik)](https://github.com/jmahlik))
- Remove `mlxtend.image` submodule with face recognition functions due to poor `dlib` support in modern environments.

New Features and Enhancements

- Document how to use `SequentialFeatureSelector` and multiclass ROC AUC.

Changes

- When [`ExhaustiveFeatureSelector`](https://rasbt.github.io/mlxtend/user_guide/feature_selection/ExhaustiveFeatureSelector/) is run with `n_jobs == 1`, joblib is now disabled, which enables more immediate (live) feedback when the `verbose` mode is enabled. ([#985](https://github.com/rasbt/mlxtend/pull/985) via [Nima Sarajpoor](https://github.com/NimaSarajpoor))
- Disabled unnecessary warning in [`EnsembleVoteClassifier`](https://rasbt.github.io/mlxtend/user_guide/classifier/EnsembleVoteClassifier/) ([#941](https://github.com/rasbt/mlxtend/issues/941))
- Fixed various documentation issues ([849](https://github.com/rasbt/mlxtend/issues/849) and [#951](https://github.com/rasbt/mlxtend/issues/951) via [Lekshmanan Natarajan](https://github.com/zuari1993))
- Fixed "Edit on GitHub" button ([1024](https://github.com/rasbt/mlxtend/issues/1024))

New Features and Enhancements

- The [`mlxtend.frequent_patterns.association_rules`](https://rasbt.github.io/mlxtend/user_guide/frequent_patterns/association_rules/) function has a new metric - Zhang's Metric, which measures both association and dissociation. ([#980](https://github.com/rasbt/mlxtend/pull/980))
- Internal [`mlxtend.frequent_patterns.fpmax`](https://rasbt.github.io/mlxtend/user_guide/frequent_patterns/association_rules/) code improvement that avoids casting a sparse DataFrame into a dense NumPy array. ([#1000](https://github.com/rasbt/mlxtend/pull/1000) via [Tim Kellogg](https://github.com/tkellogg))
- The [`plot_decision_regions`](https://rasbt.github.io/mlxtend/user_guide/plotting/plot_decision_regions/) function now has a `n_jobs` parameter to parallelize the computation. (In a particular use case, on a small dataset, there was a 21x speed-up (449 seconds vs 21 seconds on local HPC instance of 36 cores). ([#998](https://github.com/rasbt/mlxtend/pull/998) via [Khalid ElHaj](https://github.com/Ne-oL))
- Added [`mlxtend.frequent_patterns.hmine`](https://rasbt.github.io/mlxtend/user_guide/frequent_patterns/hmine/) algorithm and documentation for mining frequent itemsets using the H-Mine algorithm. ([#1020](https://github.com/rasbt/mlxtend/pull/1020) via [Fatih Sen](https://github.com/fatihsen20))

New Features and Enhancements

- The `mlxtend.evaluate.feature_importance_permutation` function has a new `feature_groups` argument to treat user-specified feature groups as single features, which is useful for one-hot encoded features. ([955](https://github.com/rasbt/mlxtend/pull/955))
- The `mlxtend.feature_selection.ExhaustiveFeatureSelector` and `SequentialFeatureSelector` also gained support for `feature_groups` with a behavior similar to the one described above. ([957](https://github.com/rasbt/mlxtend/pull/957) and [#965](https://github.com/rasbt/mlxtend/pull/965) via [Nima Sarajpoor](https://github.com/NimaSarajpoor))

Changes

- The `custom_feature_names` parameter was removed from the `ExhaustiveFeatureSelector` due to redundancy and to simplify the code base. The [`ExhaustiveFeatureSelector` documentation](http://rasbt.github.io/mlxtend/user_guide/feature_selection/ExhaustiveFeatureSelector/) illustrates how the same behavior and outcome can be achieved using pandas DataFrames. ([#957](https://github.com/rasbt/mlxtend/pull/957))

Bug Fixes

- None