Find classification edge for support vector machine (SVM) classifier

`e = edge(SVMModel,TBL,ResponseVarName)`

`e = edge(SVMModel,TBL,Y)`

`e = edge(SVMModel,X,Y)`

`e = edge(___,'Weights',weights)`

returns the classification edge
(`e`

= edge(`SVMModel`

,`TBL`

,`ResponseVarName`

)`e`

) for the support vector machine (SVM) classifier
`SVMModel`

using the predictor data in table
`TBL`

and the class labels in
`TBL.ResponseVarName`

.

The classification edge (`e`

) is a scalar value that
represents the weighted mean of the classification
margins.

returns the classification edge
(`e`

= edge(`SVMModel`

,`TBL`

,`Y`

)`e`

) for the SVM classifier `SVMModel`

using the predictor data in table `TBL`

and the class labels
in `Y`

.

For binary classification, the software defines the margin for
observation *j*, *m _{j}*, as

$${m}_{j}=2{y}_{j}f({x}_{j}),$$

where *y _{j}* ∊ {-1,1}, and

[1] Christianini, N., and J. C. Shawe-Taylor. *An
Introduction to Support Vector Machines and Other Kernel-Based Learning
Methods*. Cambridge, UK: Cambridge University Press, 2000.

`ClassificationSVM`

| `CompactClassificationSVM`

| `fitcsvm`

| `kfoldedge`

| `loss`

| `margin`

| `predict`

| `resubEdge`