JingweiToo/Wrapper-Feature-Selection-Toolbox
This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.
This toolbox helps researchers and data scientists simplify complex datasets for machine learning models. You provide a dataset with many features and their corresponding labels, and it outputs a smaller, optimized set of features that are most relevant, along with the model's accuracy. This is ideal for anyone working on data mining projects who needs to improve model performance by reducing dimensionality.
187 stars. No commits in the last 6 months.
Use this if you are a researcher or data scientist working with datasets that have too many input variables and you need to identify the most impactful ones to improve your predictive models.
Not ideal if you prefer to build feature selection algorithms from scratch or do not use MATLAB for your data analysis.
Stars
187
Forks
39
Language
MATLAB
License
BSD-3-Clause
Category
Last pushed
Mar 04, 2021
Commits (30d)
0
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