Classification margins for observations not used in training
returns
the cross-validated classification margins obtained
by m
= kfoldMargin(CVMdl
)CVMdl
, which is a cross-validated, error-correcting
output codes (ECOC) model composed of linear classification models.
That is, for every fold, kfoldMargin
estimates the
classification margins for observations that it holds out when it
trains using all other observations.
m
contains classification margins for each
regularization strength in the linear classification models that comprise CVMdl
.
uses
additional options specified by one or more m
= kfoldMargin(CVMdl
,Name,Value
)Name,Value
pair
arguments. For example, specify a decoding scheme or verbosity level.
[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.
ClassificationLinear
| ClassificationPartitionedLinearECOC
| kfoldEdge
| kfoldPredict
| margin