LinearRdDecisionFunction

java.lang.Object

org.drip.function.definition.RdToR1

org.drip.learning.svm.RdDecisionFunction

org.drip.learning.svm.LinearRdDecisionFunction

public abstract class LinearRdDecisionFunction
extends RdDecisionFunction

LinearRdDecisionFunction implements the Linear-based R^d Decision Function-Based SVM Functionality for Classification and Regression.

Module = Computational Core Module
Library = Statistical Learning
Project = Agnostic Learning Bounds under Empirical Loss Minimization Schemes
Package = Kernel SVM Decision Function Operator

Author:: Lakshmi Krishnamurthy

Constructor Summary

Constructors
Constructor	Description
`LinearRdDecisionFunction(RdGeneralizedVector gmvsPredictor, RdNormed rmnsInverseMargin, double[] adblInverseMarginWeight, double dblB)`	LinearRdDecisionFunction Constructor

Method Summary

Modifier and Type Method Description

double evaluate(double[] adblX)
Evaluate for the given Input Variates

Methods inherited from class org.drip.learning.svm.RdDecisionFunction
classify, entropyNumberUpperBounds, inverseMarginSpace, inverseMarginWeights, logEntropyNumberAsymptote, offset, optimizeClassificationHyperplane, optimizeRegressionHyperplane, predictorSpace, regress

Methods inherited from class org.drip.function.definition.RdToR1
conditionNumber, conditionNumberL2, conditionNumberLInfinity, conditionNumberLp, derivative, differential, dimension, gradient, gradientModulus, gradientModulusFunction, hessian, integrate, jacobian, maxima, minima, ValidateInput

Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details
- LinearRdDecisionFunction
  
  public LinearRdDecisionFunction(RdGeneralizedVector gmvsPredictor, RdNormed rmnsInverseMargin, double[] adblInverseMarginWeight, double dblB) throws java.lang.Exception
  
  LinearRdDecisionFunction Constructor
  
  Parameters:
  
  gmvsPredictor - The R^d Metric Input Predictor Space
  
  rmnsInverseMargin - The Inverse Margin Weights R^d L2 Space
  
  adblInverseMarginWeight - Array of Inverse Margin Weights
  
  dblB - The Offset
  
  Throws:
  
  java.lang.Exception - Thrown if the Inputs are Invalid
Method Details
- evaluate
  
  public double evaluate(double[] adblX) throws java.lang.Exception
  
  Description copied from class: RdToR1
  
  Evaluate for the given Input Variates
  
  Specified by:
  
  evaluate in class RdToR1
  
  Parameters:
  
  adblX - Array of Input Variates
  
  Returns:
  
  The Calculated Value
  
  Throws:
  
  java.lang.Exception - Thrown if the Evaluation cannot be done