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As I understand, currently only the best model from the population is being saved in the end of the iteration. This may lead to inconsistent train/test results (due to overfitting) in some setups. Blending the top n models could potentially reduce this effect.
Would you be interested in this feature for evojax? I can work on a PR. Seems like not all solvers can have this feature.
The text was updated successfully, but these errors were encountered:
As I understand, currently only the best model from the population is being saved in the end of the iteration. This may lead to inconsistent train/test results (due to overfitting) in some setups. Blending the top n models could potentially reduce this effect.
Would you be interested in this feature for evojax? I can work on a PR. Seems like not all solvers can have this feature.
The text was updated successfully, but these errors were encountered: