@Override public ParameterCostEvaluatorDerivativeFree createInternalFunction() { return new ParameterCostEvaluatorDerivativeFree( this.getResult(), this.getCostFunction() ); }
@Override public LocallyWeightedFunction<InputType, OutputType> learn( Collection<? extends InputOutputPair<? extends InputType, OutputType>> data ) { return new LocallyWeightedFunction<InputType, OutputType>( this.getKernel(), data, this.getLearner() ); }
@Override public ParameterCostEvaluatorDerivativeBased createInternalFunction() { return new ParameterCostEvaluatorDerivativeBased( this.getResult(),(DifferentiableCostFunction) this.getCostFunction() ); }
/** * Creates a new instance of LinearRegression * @param inputToVectorMap * Function that maps the InputType to a Vector */ public LinearBasisRegression( Evaluator<? super InputType, Vector> inputToVectorMap ) { this.setInputToVectorMap( inputToVectorMap ); this.setUsePseudoInverse( true ); }
@Override public ParameterDifferentiableCostMinimizer clone() { return (ParameterDifferentiableCostMinimizer) super.clone(); }
/** * Creates a new instance of MultivariateLinearRegression */ public MultivariateLinearRegression() { this.setUsePseudoInverse(true); }
@Override public double getTestStatistic() { return this.getChiSquare(); }
@Override public ParameterCostEvaluatorDerivativeFree createInternalFunction() { return new ParameterCostEvaluatorDerivativeFree( this.getResult(), this.getCostFunction() ); }
@Override public LocallyWeightedFunction<InputType, OutputType> learn( Collection<? extends InputOutputPair<? extends InputType, OutputType>> data ) { return new LocallyWeightedFunction<InputType, OutputType>( this.getKernel(), data, this.getLearner() ); }
@Override public ParameterCostEvaluatorDerivativeBased createInternalFunction() { return new ParameterCostEvaluatorDerivativeBased( this.getResult(),(DifferentiableCostFunction) this.getCostFunction() ); }
/** * Creates a new instance of LinearRegression * @param inputToVectorMap * Function that maps the InputType to a Vector */ public LinearBasisRegression( Evaluator<? super InputType, Vector> inputToVectorMap ) { this.setInputToVectorMap( inputToVectorMap ); this.setUsePseudoInverse( true ); }
@Override public ParameterDifferentiableCostMinimizer clone() { return (ParameterDifferentiableCostMinimizer) super.clone(); }
/** * Creates a new instance of MultivariateLinearRegression */ public MultivariateLinearRegression() { this.setUsePseudoInverse(true); }
@Override public double getTestStatistic() { return this.getChiSquare(); }
@Override public ParameterCostEvaluatorDerivativeFree createInternalFunction() { return new ParameterCostEvaluatorDerivativeFree( this.getResult(), this.getCostFunction() ); }
@Override public LocallyWeightedFunction<InputType, OutputType> learn( Collection<? extends InputOutputPair<? extends InputType, OutputType>> data ) { return new LocallyWeightedFunction<InputType, OutputType>( this.getKernel(), data, this.getLearner() ); }
@Override public ParameterCostEvaluatorDerivativeBased createInternalFunction() { return new ParameterCostEvaluatorDerivativeBased( this.getResult(),(DifferentiableCostFunction) this.getCostFunction() ); }
@Override public ParameterDerivativeFreeCostMinimizer clone() { return (ParameterDerivativeFreeCostMinimizer) super.clone(); }
/** * Creates a new instance of MultivariateLinearRegression */ public MultivariateLinearRegression() { this.setUsePseudoInverse(true); }
@Override public ParameterDifferentiableCostMinimizer clone() { return (ParameterDifferentiableCostMinimizer) super.clone(); }