CombinationOptimizationContextStopAtIntermediateIteration Method

protected override bool StopAtIntermediateIteration(
	int iteration,
	LinkedList<double> levels,
	LinkedList<DoubleMatrix> parameters
)

Protected Overrides Function StopAtIntermediateIteration ( 
	iteration As Integer,
	levels As LinkedList(Of Double),
	parameters As LinkedList(Of DoubleMatrix)
) As Boolean

protected:
virtual bool StopAtIntermediateIteration(
	int iteration, 
	LinkedList<double>^ levels, 
	LinkedList<DoubleMatrix^>^ parameters
) override

abstract StopAtIntermediateIteration : 
        iteration : int * 
        levels : LinkedList<float> * 
        parameters : LinkedList<DoubleMatrix> -> bool 
override StopAtIntermediateIteration : 
        iteration : int * 
        levels : LinkedList<float> * 
        parameters : LinkedList<DoubleMatrix> -> bool 

Parameters

iteration

Type: SystemInt32
The current iteration identifier.

levels

Type: System.Collections.GenericLinkedListDouble
The performance levels achieved in previous iterations by a SystemPerformanceOptimizer executing in this context.

parameters

Type: System.Collections.GenericLinkedListDoubleMatrix
The sampling parameters applied in previous iterations by a SystemPerformanceOptimizer executing in this context.

Return Value

At intermediate iterations, the algorithm will stop under the following conditions.

A CombinationOptimizationContext never stops before executing a number of iterations less than MinimumNumberOfIterations, and always stops if such number is greater than or equal to MaximumNumberOfIterations.

For intermediate iterations, method StopAtIntermediateIteration(Int32, LinkedListDouble, LinkedListDoubleMatrix) is called to check if a Cross-Entropy program executing in this context should stop or not.

In a CombinationOptimizationContext, the method analyzes the currently updated reference parameter, say as follows. Let be MinimumNumberOfIterations, and defines as the set of indexes in corresponding to its largest probabilities, where is CombinationDimension. If condition



can be verified, the method returns true; otherwise false is returned. The algorithm thus converges if the indexes of the largest probabilities coincide times in a row of iterations.

Reference