Test error lower than training error
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Would appreciate your input on this. I am constructing a regression model with the help of genetic programming. 

If my RMSE on test data is (much) lower than my RMSE on training data for a 1:5 ratio of data, should I be worried? 

The test data is drawn randomly without replacement from a set of 24 data points. The model was built using genetic programming technique so the number of features, modeling framework etc vary as I minimize the training RMSE regularized by the number of nodes in the GP tree. 

Is the model underfitted? Or should I have minimized MSE instead of RMSE (I thought it would be the same as MSE is positive and the minimum of MSE would coincide with the minimum of RMSE assuming the optimizer is good enough to find the minimum)? 

Tks
