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Classification edge for cross-validated ECOC model

`edge = kfoldEdge(CVMdl)`

`edge = kfoldEdge(CVMdl,Name,Value)`

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

= kfoldEdge(`CVMdl`

)`ClassificationPartitionedECOC`

) `CVMdl`

. For every
fold, `kfoldEdge`

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

contains both sets of observations.

returns the classification edge with additional options specified by one or more
name-value pair arguments. For example, specify the number of folds, decoding
scheme, or verbosity level.`edge`

= kfoldEdge(`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`

| `edge`

| `fitcecoc`

| `kfoldMargin`

| `kfoldPredict`

| `statset`