duxuhao/Feature-Selection
Features selector based on the self selected-algorithm, loss function and validation method
This tool helps data scientists and machine learning engineers streamline the process of choosing the most impactful features for their predictive models. You input your raw dataset and a machine learning algorithm, and it outputs an optimized list of features that improve model performance. It's designed for practitioners building robust and efficient predictive systems.
679 stars. No commits in the last 6 months.
Use this if you need to systematically select the best features for your machine learning models to improve accuracy or reduce complexity, especially when working with large datasets and many potential input variables.
Not ideal if you are looking for an automated, black-box solution without needing to specify your own machine learning algorithms, loss functions, or validation methods.
Stars
679
Forks
198
Language
Python
License
MIT
Category
Last pushed
May 08, 2019
Commits (30d)
0
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