# Root MSE or (RMSE) in regression model

I was calculating the root mean squared error for a regressive model, and while calculating, its mean squared error (MSE) came out to be less than 1 (>0), and its root (the root mean squared error, RMSE) as obvious came out to be greater than it. What does that mean?
like MSE = 0.0929285270191
and hence, RMSE = 0.894951677992

How do I see it?
Was there any problem in calculation or training of the model?
Is it that MSE is coming out very less that is not likely possible?

• Martin Kramer in the answers is right. But what is your question, really? I cannot understand it. Jan 25, 2017 at 17:56

It means that the $$MSE$$ is less than $$1$$, which might be spectacular performance, dreadful performance, or somewhere in between, depending on your problem. Performance out of context is fairly meaningless.
That's just how the square root works: $$x\in(0, 1)\implies x < \sqrt{x}$$.
Note that the example values you gave are not possible, as the $$RMSE$$ corresponding to your $$MSE = 0.0929285270191$$ would be $$RMSE=\sqrt{0.0929285270191}\approx 0.305$$, though I think you just picked two numbers arbitrarily that satisfy $$MSE < RMSE$$.