QuasiNewtonTrainer.Error (JMSL Numerical Library)

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JMSL^TM Numerical Library 6.1

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com.imsl.datamining.neural
Interface QuasiNewtonTrainer.Error

Error function to be minimized by trainer. This trainer attempts to solve the problem

$min_{w} sum_{i=0}^{n-1} e(y_i, hat{y}_i)$

where w are the weights, n is the number of training patterns,

is a training target output and $hat{y}_i$ is its forecast value.

This interface defines the function and its derivative with respect to its computed value, .

Method Summary
`double`	`error(double[] computed, double[] expected)` Returns the contribution to the error from a single training output target.
`double[]`	`errorGradient(double[] computed, double[] expected)` Returns the derivative of the error function with respect to the forecast output.

Method Detail

double error(double[] computed,
             double[] expected)

Returns the contribution to the error from a single training output target. This is the function $e(y_i, hat{y}_i)$ .

Parameters:: computed - A double representing the computed value.; expected - A double representing the expected value.
Returns:: A double representing the contribution to the error from a single training output target.

double[] errorGradient(double[] computed,
                       double[] expected)

Returns the derivative of the error function with respect to the forecast output.

Parameters:: computed - A double representing the computed value.; expected - A double representing the expected value.
Returns:: A double representing the derivative of the error function with respect to the forecast output.