Community Articles

These articles, tutorials, and walkthroughs are written outside the official project documentation by people using or contributing to sklearn-genetic-opt.

If you publish an article about the project, open a pull request adding it to the bottom of this list. Entries are kept in submission order so the page recognizes contributors fairly without ranking articles.

Please include:

• the article title
• the author name or GitHub handle
• the publication platform
• a short description of what the article teaches

Links should be relevant to sklearn-genetic-opt, respectful, and not primarily promotional.

Articles

1. Hyperparameters Tuning: From Grid Search to Optimization
   Rodrigo Arenas on Medium. Introduces hyperparameter tuning workflows and the motivation for moving beyond exhaustive grid search.

2. Evolutionary Feature Selection for Machine Learning
   Rodrigo Arenas on Medium. Explains how evolutionary search can be used for wrapper-based feature selection in machine learning projects.

3. sklearn-genetic-opt 0.13: What Five Years of Genetic Search Taught Me
   Rodrigo Arenas on Medium. Shares lessons from the 0.13 release and the evolution of the project over several years.

4. GASearchCV vs RandomizedSearchCV: When Evolutionary Search Pays Off
   Andrian Balanescu (@andrianbalanesq) on GitHub. Compares GASearchCV against RandomizedSearchCV on a noisy XGBoost task with a runnable notebook.

5. From Scratch to Streamlined: Comparing My Hand-Built Genetic Algorithm with sklearn-genetic
   William on William's Data Science Blog. Walks through building a genetic feature-selection algorithm from scratch, then shows how sklearn-genetic-opt replaces over a hundred lines of custom code with a single library call.

6. Hyperparameter Tuning with GASearchCV on a Real Dataset
   Saadgi Puniwala on dev.to. A hands-on comparison of GASearchCV against GridSearchCV on the UCI Student Performance dataset, including fitness evolution and search-space visualizations.