This function computes the root-mean-square error.
Arguments
- ...
arguments to mean_squared_error
Value
the root-mean-square error, a positive double or a vector of positive double values,
one for each response, if response has multiple output values and multi = "raw"
Details
The root-mean-square error (RMSE) is a measure of errors based on squared losses. It is defined as the squared root of the mean_squared_error:
$$RMSE(y,\hat{y}) = \sqrt{MSE(y,\hat{y})} = \sqrt{\frac{1}{n}\sum_{i=1}^{n} (y_{i} - \hat{y}_{i})^{2}}$$
If observation weights are provided, then the weighted root mean squared error is computed as
$$wRMSE(w,y,\hat{y}) = \sqrt{wMSE(w,y,\hat{y})} = \sqrt{\frac{1}{\sum_{i=1}^{n} w_{i}}\sum_{i=1}^{n} w_{i} * (y_{i} - \hat{y}_{i})^{2}}$$
This function is a shortcut for mean_squared_error(root = TRUE, ...).