public abstract class LinearRdDecisionFunction extends RdDecisionFunction
| Constructor and Description |
|---|
LinearRdDecisionFunction(RdGeneralizedVector gmvsPredictor,
RdNormed rmnsInverseMargin,
double[] adblInverseMarginWeight,
double dblB)
LinearRdDecisionFunction Constructor
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| Modifier and Type | Method and Description |
|---|---|
double |
evaluate(double[] adblX)
Evaluate for the given Input Variates
|
classify, entropyNumberUpperBounds, inverseMarginSpace, inverseMarginWeights, logEntropyNumberAsymptote, offset, optimizeClassificationHyperplane, optimizeRegressionHyperplane, predictorSpace, regressderivative, differential, dimension, gradient, gradientModulus, gradientModulusFunction, hessian, integrate, jacobian, maxima, minima, ValidateInputpublic LinearRdDecisionFunction(RdGeneralizedVector gmvsPredictor, RdNormed rmnsInverseMargin, double[] adblInverseMarginWeight, double dblB) throws java.lang.Exception
gmvsPredictor - The R^d Metric Input Predictor SpacermnsInverseMargin - The Inverse Margin Weights R^d L2 SpaceadblInverseMarginWeight - Array of Inverse Margin WeightsdblB - The Offsetjava.lang.Exception - Thrown if the Inputs are Invalidpublic double evaluate(double[] adblX)
throws java.lang.Exception
RdToR1