Resubstitution classification loss for multiclass error-correcting output codes (ECOC) model

returns the classification loss by resubstitution (`L`

= resubLoss(`Mdl`

)`L`

) for the
multiclass error-correcting output codes (ECOC) model `Mdl`

using the
training data stored in `Mdl.X`

and the corresponding class labels stored
in `Mdl.Y`

. By default, `resubLoss`

uses the classification error to compute `L`

.

The classification loss (`L`

) is a generalization or resubstitution
quality measure. Its interpretation depends on the loss function and weighting scheme, but
in general, better classifiers yield smaller classification loss values.

returns the classification loss with additional options specified by one or more name-value
pair arguments. For example, you can specify the loss function, decoding scheme, and
verbosity level.`L`

= resubLoss(`Mdl`

,`Name,Value`

)

[1] Allwein, E., R. Schapire, and Y. Singer. “Reducing
multiclass to binary: A unifying approach for margin classiﬁers.” *Journal of
Machine Learning Research*. Vol. 1, 2000, pp. 113–141.

[2] Escalera, S., O. Pujol, and P. Radeva. “On the decoding
process in ternary error-correcting output codes.” *IEEE Transactions on
Pattern Analysis and Machine Intelligence*. Vol. 32, Issue 7, 2010, pp.
120–134.

[3] Escalera, S., O. Pujol, and P. Radeva. “Separability of
ternary codes for sparse designs of error-correcting output codes.” *Pattern
Recogn*. Vol. 30, Issue 3, 2009, pp. 285–297.

`ClassificationECOC`

| `fitcecoc`

| `loss`

| `predict`

| `resubPredict`