- 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??
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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??
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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.
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