Classify a set of observations and associated frequencies and weights using the linear or quadratic discriminant functions generated during the training process.

Namespace: Imsl.Stat
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.0.0

Syntax

C#
public void Classify(
	double[,] x,
	int[] frequencies,
	double[] weights
)
Visual Basic (Declaration)
Public Sub Classify ( _
	x As Double(,), _
	frequencies As Integer(), _
	weights As Double() _
)
Visual C++
public:
void Classify(
	array<double,2>^ x, 
	array<int>^ frequencies, 
	array<double>^ weights
)

Parameters

x
Type: array< System..::.Double ,2>[,](,)[,]
A double matrix containing the observations with at least nVariables columns. The first nVariables columns correspond to the variables. Reclassification does not require group numbers be present. Any additional columns will be ignored.
frequencies
Type: array< System..::.Int32 >[]()[]
An int array containing the associated frequencies for each observation.
weights
Type: array< System..::.Double >[]()[]
A double array containing the associated weights for each observation

Remarks

An InvalidOperationException is thrown if the leave-out-one classification method is chosen.

Exceptions

ExceptionCondition
Imsl.Stat..::.SumOfWeightsNegException is thrown when the sum of the weights have become negative.
Imsl.Stat..::.EmptyGroupException is thrown when there are no observations in a group.
Imsl.Stat..::.CovarianceSingularException is thrown when the variance-covariance matrix is singular.

See Also