JMSLTM Numerical Library 4.0

com.imsl.datamining.neural
Class QuasiNewtonTrainer.GradObjective

java.lang.Object
  extended bycom.imsl.datamining.neural.QuasiNewtonTrainer.Objective
      extended bycom.imsl.datamining.neural.QuasiNewtonTrainer.GradObjective
All Implemented Interfaces:
MinUnconMultiVar.Function, MinUnconMultiVar.Gradient
Direct Known Subclasses:
QuasiNewtonTrainer.BlockGradObjective
Enclosing class:
QuasiNewtonTrainer

protected class QuasiNewtonTrainer.GradObjective
extends QuasiNewtonTrainer.Objective
implements MinUnconMultiVar.Gradient

The Objective class is passed to the optimizer.


Field Summary
protected  int nFunctionEvaluations
           
protected  int nObs
           
protected  int nY
           
 
Method Summary
 void gradient(double[] weights, double[] gradient)
          Public interface for the gradient of the multivariate function to be minimized.
 
Methods inherited from class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
f
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface com.imsl.math.MinUnconMultiVar.Function
f
 

Field Detail

nFunctionEvaluations

protected int nFunctionEvaluations

nObs

protected int nObs

nY

protected int nY
Method Detail

gradient

public void gradient(double[] weights,
                     double[] gradient)
Description copied from interface: MinUnconMultiVar.Gradient
Public interface for the gradient of the multivariate function to be minimized.

Specified by:
gradient in interface MinUnconMultiVar.Gradient
Parameters:
weights - a double array, the point at which the gradient of the function is to be evaluated
gradient - a double array, the value of the gradient of the function at x

JMSLTM Numerical Library 4.0

Copyright 1970-2006 Visual Numerics, Inc.
Built June 1 2006.