[Feature Request]: Feature Selection for Machine Learning with Genetic Algorithm #338
Description
Is there an existing issue for this?
- I have searched the existing issues
Feature Description
- Data Collection: Use an existing dataset with multiple features.
- Initialize Population: Create an initial population of feature subsets.
- Fitness Function: Define a fitness function based on model performance (e.g., accuracy, F1 score).
- Selection: Select the best feature subsets for crossover.
- Crossover: Combine feature subsets to create new subsets.
- Mutation: Introduce small changes to feature subsets to maintain diversity.
- Evaluation: Assess the performance of the selected feature subsets on the model.
Use Case
This project uses a genetic algorithm to perform feature selection for a machine learning model. The goal is to identify the most relevant features that contribute to model performance.
Benefits
No response
Priority
High
Record
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- I'm willing to provide further clarification or assistance if needed.