sklearn-genetic-opt 0.13.3

This release focuses on making search-space authoring easier, checkpointing safer, errors clearer, and the documentation/release flow cleaner.

Highlights

Search-space conversion helper: from_sklearn_space converts common RandomizedSearchCV-style spaces into native Integer, Continuous, and Categorical dimensions. It supports list-like categorical choices plus scipy.stats.randint, uniform, loguniform, and reciprocal frozen distributions.
Estimator presets: new starter spaces for RandomForestClassifier, RandomForestRegressor, HistGradientBoostingClassifier, HistGradientBoostingRegressor, LogisticRegression, SVC, XGBClassifier, and XGBRegressor. Presets support profile="fast", "balanced", or "wide" and a prefix argument for sklearn pipelines.
Checkpointing fixes: ModelCheckpoint and resume flows now build constructor-compatible estimator state more reliably, including GAFeatureSelectionCV support.
Better validation and error messages across search spaces, plotting helpers, callbacks, MLflow optional dependency handling, and scheduler adapters.
Docs cleanup: VitePress is now the single docs tree for generated images and release-facing docs.

Added from_sklearn_space for converting sklearn/scipy-style search spaces into native sklearn-genetic-opt dimensions.
Added estimator preset helpers for common classifiers and regressors, including pipeline-friendly prefixes.
Added --use-cache / --no-use-cache to benchmarks/benchmark_fit.py, threading the option through GASearchCV and GAFeatureSelectionCV benchmark builders.
Added clearer successful-save output for ModelCheckpoint.
Improved internal score ranking utilities to handle NaN values consistently.

Fixed ModelCheckpoint state generation for GAFeatureSelectionCV and removed duplicate param_grid state.
Fixed random_state=0 handling for Integer and Continuous dimensions.
Fixed Categorical priors being ignored during sampling.
Fixed fitness cache restoration during checkpoint resume.
Fixed clearer validation for error_score during estimator construction.
Fixed and improved several plotting helper errors, including invalid top_k, unavailable metrics, unfitted estimators, and missing history fields.
Improved search-space validation for warm-start configs, unsupported scipy distributions, feature-name count mismatches, preset prefixes, and invalid param_grid entries.
Improved optional dependency messaging when MLflow is not installed.

Added and expanded documentation for estimator presets, search-space conversion, pipeline preset prefixes, callbacks, troubleshooting, and community articles.
Added CITATION.cff and improved README citation guidance, including a BibTeX example.
Added internal Markdown link checking for versioned VitePress docs and root docs links.
Removed legacy docs/images duplication; generated figures now live under docs-vitepress/public/images.
Added pre-commit configuration for Black and basic hygiene checks.
Built and validated release artifacts with python -m build and twine check.

pip install -U sklearn-genetic-opt==0.13.3

Huge thanks to everyone who contributed code, tests, docs, reviews, and release polish for this version: