Find classification error for support vector machine (SVM) classifier
returns the classification error (see Classification Loss), a
scalar representing how well the trained support vector machine (SVM) classifier
(L
= loss(SVMModel
,TBL
,ResponseVarName
)SVMModel
) classifies the predictor data in table
TBL
compared to the true class labels in
TBL.ResponseVarName
.
loss
normalizes the class probabilities in
TBL.ResponseVarName
to the prior class probabilities that
fitcsvm
used for training, stored
in the Prior
property of SVMModel
.
The classification loss (L
) is a generalization or
resubstitution quality measure. Its interpretation depends on the loss function
and weighting scheme, but, in general, better classifiers yield smaller
classification loss values.
specifies options using one or more name-value pair arguments in addition to the
input arguments in previous syntaxes. For example, you can specify the loss
function and the classification weights.L
= loss(___,Name,Value
)
[1] Hastie, T., R. Tibshirani, and J. Friedman. The Elements of Statistical Learning, second edition. Springer, New York, 2008.
ClassificationSVM
| CompactClassificationSVM
| fitcsvm
| predict