mse
Description
The half mean squared error operation computes the half mean squared error loss between network predictions and target values for regression tasks.
The loss is calculated using the following formula
where Xi is the network prediction, Ti is the target value, M is the total number of responses in X (across all observations), and N is the total number of observations in X.
Note
This function computes the half mean squared error loss between predictions and
targets stored as dlarray
data. If
you want to calculate the half mean squared error loss within a layerGraph
object
or Layer
array for
use with trainNetwork
, use regressionLayer
.
To train a network using the trainnet
function with mean square error loss, set the loss function to
"mse"
.
Examples
Input Arguments
Output Arguments
Algorithms
Extended Capabilities
Version History
Introduced in R2019b