mse(ŷ, y; agg = mean)

Return the loss corresponding to mean square error:

			agg((ŷ .- y) .^ 2)

See also: mae , msle , crossentropy .

Example

			julia> y_model = [1.1, 1.9, 3.1];

julia> y_true = 1:3;

julia> Flux.mse(y_model, y_true)
0.010000000000000018