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I am running k-fold cross validation on my training data, and then choosing the best set of hyper parameters, re-training on the training data and testing on a new (unseen) testing data. I am getting the following testing results (results on the unseen data):

R^2: 1.000
Adj R^2: 1.000
RMSE: 0.081
MSE: 0.007
MAE: 0.045
MAPE: 0.058

Can $R^2$ have a value of 1.00 but RMSE have a value of 0.081? Doesn't an $R^2$ of value 1 indicate no errors at all?

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The $R^2$ value is rounded to 3 decimal places. If the exact $R^2$ is $\ge$0.9995, it would then be reported as 1.000.

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    $\begingroup$ Thank you so much @mkt, thats exactly whats happening. $\endgroup$ – Hiyam Sep 30 '19 at 8:40

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