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Classification margins for multiclass error-correcting output codes (ECOC) model

`m = margin(Mdl,tbl,ResponseVarName)`

`m = margin(Mdl,tbl,Y)`

`m = margin(Mdl,X,Y)`

`m = margin(___,Name,Value)`

returns the classification margins
(`m`

= margin(`Mdl`

,`tbl`

,`ResponseVarName`

)`m`

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

using the predictor data in table `tbl`

and the class labels in `tbl.ResponseVarName`

.

specifies options using one or more name-value pair arguments in addition to any of the
input argument combinations in previous syntaxes. For example, you can specify a decoding
scheme, binary learner loss function, and verbosity level.`m`

= margin(___,`Name,Value`

)

To compare the margins or edges of several ECOC classifiers, use template objects to specify a common score transform function among the classifiers during training.

[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`

| `CompactClassificationECOC`

| `edge`

| `fitcecoc`

| `loss`

| `predict`

| `resubMargin`