- Run GA multiple times and take the average of all the best fitness values.
- Increase population size and number of generations which will explore a larger solution space and give a better result.
- Change and experiment the type of crossovers and mutations you are using. Please follow this link to know more about it: https://www.mathworks.com/help/gads/genetic-algorithm-options.html
- Use elitism to ensure that the best solutions are carried over to the next generation.
Termination criterion for Genetic Algorithm when used in context of feature selection??
1 view (last 30 days)
Show older comments
I have tried for 50 iterations but on running the Matlab code the best fitness value of all iterations is coming out to be different at different times. How will I decide which will be the best features in such a condition.
Getting different best feature set for same number of iterations. How results should be interpreted so that I can come to a Termination criterion??
0 Comments
Answers (1)
Prateekshya
on 19 Jul 2024
Edited: Prateekshya
on 19 Jul 2024
Hello Purti,
I understand that you are getting different output in different runs of Genetic Algorithm. This is a common behavior due to the stoachastic nature of GA which gives you near-optimal (not exactly optimal) solutions. Here are some strategies to make the results more consistent:
I hope this helps!
Thank you.
0 Comments
See Also
Categories
Find more on Genetic Algorithm in Help Center and File Exchange
Products
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!