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Classification margins for cross-validated ECOC model

`margin = kfoldMargin(CVMdl)`

`margin = kfoldMargin(CVMdl,Name,Value)`

returns classification margins obtained by the
cross-validated ECOC model (`margin`

= kfoldMargin(`CVMdl`

)`ClassificationPartitionedECOC`

)
`CVMdl`

. For every fold, `kfoldMargin`

computes classification margins for validation-fold observations using an ECOC model
trained on training-fold observations. `CVMdl.X`

contains both sets
of observations.

returns classification margins with additional options specified by one or more
name-value pair arguments. For example, specify the binary learner loss function,
decoding scheme, or verbosity level.`margin`

= kfoldMargin(`CVMdl`

,`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`

| `ClassificationPartitionedECOC`

| `fitcecoc`

| `kfoldEdge`

| `kfoldPredict`

| `margin`

| `statset`