pedbrgs/PyCCEA
A Python package of cooperative co-evolutionary algorithms for feature selection in high-dimensional data.
This tool helps researchers and practitioners in machine learning and data science identify the most relevant features in very large datasets. It takes a dataset with many columns (features) and a target variable, and outputs a smaller, optimized set of features that are most important for building accurate predictive models. It's designed for anyone working with high-dimensional data who needs to simplify their models or improve their performance.
Available on PyPI.
Use this if you are working with datasets that have hundreds or thousands of features and you need to select the most impactful ones to build more efficient and accurate predictive models.
Not ideal if your datasets are small, have only a few features, or if you are not involved in building machine learning models.
Stars
15
Forks
2
Language
Python
License
MIT
Category
Last pushed
Feb 23, 2026
Commits (30d)
0
Dependencies
12
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