"The optimization attempts to minimize the cross-validation loss (error) for fitcecoc by varying the parameters. For information about cross-validation loss in a different context, see Classification Loss. "
If you click on "Classification Loss" it tells you about the multiclass loss function.
net = load('mynet.mat'); %this returns my previsouly trained SeriesNetwork object
Not exactly. The output of load applied to a mat file, is a struct that has one field for each variable loaded. So you would need net.net where the first net is the struct returned from load and the second is the variable loaded.
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