Back to Adaptive Vision Library website

You are here: Start » Function Reference » Support Vector Machines » SVM_ClassifySingle


Header: AVL.h
Namespace: avl
Module: FoundationPro

Classifies input features based on a trained model


void avl::SVM_ClassifySingle
	const avl::SvmModel& inSvmModel,
	const atl::Array<float>& inVector,
	int& outPrediction,
	atl::Optional<atl::Array< int >& > outModelClasses = atl::NIL,
	atl::Optional<atl::Array<float>& > outClassProbabilities = atl::NIL


Name Type Default Description
inSvmModel const SvmModel& Input trained model
inVector const Array<float>& Data vector of unknown class
outPrediction int& Predicted classes
outModelClasses Optional<Arrayint >& > NIL All known model classes in order
outClassProbabilities Optional<Array<float>& > NIL For each data vector the probability of belonging to each class

Optional Outputs

The computation of following outputs can be switched off by passing value atl::NIL to these parameters: outModelClasses, outClassProbabilities.

Read more about Optional Outputs.


The operation predicts classes for the given data points. It takes a data vector (inVector) as an argument. The vector has to be of the same size as vectors used for training the model. The operation outputs predicted class (outPrediction) for the data vector.
outModelClasses are all class labels encountered during training.
outClassProbabilities provides, for the input vector, estimated probability belonging to each class. Precisely, the value under index i denotes probability of given vector belonging to the class outModelClasses[i].


List of possible exceptions:

Error type Description
DomainError Incorrect vector size in SVM_ClassifySingle
DomainError Incorrect, uninitialized or not trained SvmModel in SVM_ClassifySingle.

See Also