[Feature Request]: Feature Selection for Machine Learning with Genetic Algorithm

[ashis2004]

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

• I agree to follow this project's Code of Conduct
• I'm a GSSOC contributor
• I want to work on this issue
• I'm willing to provide further clarification or assistance if needed.

[ashis2004]

@sanjay-kv pls assign it me

[github-actions]

Hello @ashis2004! Your issue #338 has been closed. Thank you for your contribution!