How close does my testing accuracy need to be to my training accuracy for ML model

Question

I've built a Random Forrest ML model. My train accuracy is around 97% and my test accuracy is around 85%.

Is this normal or is this too big of a difference? I know there is probably overfitting, but if the test accuracy is high at 85%, does it matter?

Thank you.

Golden Lion · Answer 1 · 2022-06-03T17:04:02.610

check performance by using cross validation. cross validation helps you see how your model will perform with new data. https://stats.stackexchange.com/questions/111968/random-forest-how-to-handle-overfitting

check your model for overfitting using mean squared error (regressor)

check for model overfitting with a (classifier)

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