I would like to make a related suggestion but instead of focusing on the upper
bound for the number of trees rather set choosing the lower bound. From a
theoretical perspective, it doesn't make sense to me how fewer trees can result
in a better performing random forest model in terms of generali
> Take random forest as example, if I give estimator from 10 to 1(10,
> 100, 1000, 1) into grid search.
> Based on the result, I found estimator=100 is the best, but I don't know
> lower or greater than 100 is better.
> How should I decide? brute force or any tools better than GridSearchCV?
Take random forest as example, if I give estimator from 10 to 1(10,
100, 1000, 1) into grid search.
Based on the result, I found estimator=100 is the best, but I don't know
lower or greater than 100 is better.
How should I decide? brute force or any tools better than GridSearchCV?
thx
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