Uses of Interface

Packages that use DifferentiableEvaluator
gov.sandia.cognition.learning.algorithm.minimization.line Provides line (scalar) minimization algorithms. 
gov.sandia.cognition.learning.algorithm.regression Provides regression algorithms, such as Linear Regression. 
gov.sandia.cognition.learning.function.scalar Provides functions that output real numbers. 
gov.sandia.cognition.learning.function.vector Provides functions that output vectors. 
gov.sandia.cognition.math Provides classes for mathematical computation. 
gov.sandia.cognition.math.matrix Provides interfaces and classes for linear algebra. 
gov.sandia.cognition.statistics Provides the inheritance hierarchy for general statistical methods and distributions. 
gov.sandia.cognition.statistics.bayesian Provides algorithms for computing Bayesian estimates of parameters. 
gov.sandia.cognition.statistics.distribution Provides statistical distributions. 
gov.sandia.cognition.statistics.method Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods. 

Uses of DifferentiableEvaluator in gov.sandia.cognition.learning.algorithm.minimization.line

Classes in gov.sandia.cognition.learning.algorithm.minimization.line that implement DifferentiableEvaluator
 class DirectionalVectorToDifferentiableScalarFunction
          Creates a truly differentiable scalar function from a differentiable Vector function, instead of using a forward-differences approximation to the derivative like DirectionalVectorToScalarFunction does.
 class DirectionalVectorToScalarFunction
          Maps a vector function onto a scalar one by using a directional vector and vector offset, and the parameter to the function is a scalar value along the direction from the start-point offset.
 class LineMinimizerDerivativeBased.InternalFunction
          Internal function used to map/remap/unmap the search direction.

Constructors in gov.sandia.cognition.learning.algorithm.minimization.line with parameters of type DifferentiableEvaluator
DirectionalVectorToDifferentiableScalarFunction(DifferentiableEvaluator<? super Vector,? extends Double,Vector> vectorScalarFunction, Vector vectorOffset, Vector direction)
          Creates a new instance of DirectionalVectorToDifferentiableScalarFunction

Uses of DifferentiableEvaluator in gov.sandia.cognition.learning.algorithm.regression

Classes in gov.sandia.cognition.learning.algorithm.regression that implement DifferentiableEvaluator
static class ParameterDerivativeFreeCostMinimizer.ParameterCostEvaluatorDerivativeFree
          Function that maps the parameters of an object to its inputs, so that minimization algorithms can tune the parameters of an object against a cost function.
static class ParameterDifferentiableCostMinimizer.ParameterCostEvaluatorDerivativeBased
          Function that maps the parameters of an object to its inputs, so that minimization algorithms can tune the parameters of an object against a cost function.

Fields in gov.sandia.cognition.learning.algorithm.regression with type parameters of type DifferentiableEvaluator
static FunctionMinimizer<Vector,Double,DifferentiableEvaluator<? super Vector,Double,Vector>> ParameterDifferentiableCostMinimizer.DEFAULT_FUNCTION_MINIMIZER
          Default function minimizer, FunctionMinimizerBFGS with LineMinimizerBacktracking

Constructor parameters in gov.sandia.cognition.learning.algorithm.regression with type arguments of type DifferentiableEvaluator
ParameterDerivativeFreeCostMinimizer(FunctionMinimizer<Vector,Double,? super DifferentiableEvaluator<Vector,Double,Vector>> minimizer)
          Creates a new instance of ParameterDerivativeFreeCostMinimizer
ParameterDifferentiableCostMinimizer(FunctionMinimizer<Vector,Double,? super DifferentiableEvaluator<Vector,Double,Vector>> minimizer)
          Creates a new instance of ParameterDerivativeFreeCostMinimizer

Uses of DifferentiableEvaluator in gov.sandia.cognition.learning.function.scalar

Subinterfaces of DifferentiableEvaluator in gov.sandia.cognition.learning.function.scalar
static interface PolynomialFunction.ClosedForm
          Describes functionality of a closed-form algebraic polynomial function

Classes in gov.sandia.cognition.learning.function.scalar that implement DifferentiableEvaluator
 class AtanFunction
          Returns the element-wise arctangent of the input vector, compressed between -maxMagnitude and maxMagnitude (instead of just -PI/2 and PI/2)
 class CosineFunction
          A closed-form cosine function.
 class IdentityScalarFunction
          A univariate scalar identity function: f(x) = x.
 class LinearFunction
          This function acts as a simple linear function of the form f(x) = m*x + b.
 class PolynomialFunction
          A single polynomial term specified by a real-valued exponent.
static class PolynomialFunction.Cubic
          Algebraic treatment for a polynomial of the form y(x) = q0 + q1*x + q2*x^2 + q3*x^3
static class PolynomialFunction.Linear
          Utilities for algebraic treatment of a linear polynomial of the form y(x) = q0 + q1*x
static class PolynomialFunction.Quadratic
          Utilities for algebraic treatment of a quadratic polynomial of the form y(x) = q0 + q1*x + q2*x^2.
 class SigmoidFunction
          An implementation of a sigmoid squashing function.

Uses of DifferentiableEvaluator in gov.sandia.cognition.learning.function.vector

Classes in gov.sandia.cognition.learning.function.vector that implement DifferentiableEvaluator
 class DifferentiableGeneralizedLinearModel
          A GradientDescenable version of a GeneralizedLinearModel, in other words, a GeneralizedLinearModel where the squashing function is differentiable
 class ElementWiseDifferentiableVectorFunction
          An ElementWiseVectorFunction that is also a DifferentiableVectorFunction
 class LinearVectorFunction
          The LinearFunction class is a simple VectorFunction that just scales the given input vector by a scalar value.
 class MultivariateDiscriminant
          Allows learning algorithms (vectorizing, differentiating) on a matrix*vector multiply.
 class MultivariateDiscriminantWithBias
          A multivariate discriminant (matrix multiply) plus a constant vector that gets added to the output of the discriminant.

Uses of DifferentiableEvaluator in gov.sandia.cognition.math

Subinterfaces of DifferentiableEvaluator in gov.sandia.cognition.math
 interface ClosedFormDifferentiableEvaluator<InputType,OutputType,DerivativeType>
          A differentiable function that has a closed-form derivative.
 interface DifferentiableUnivariateScalarFunction
          A differentiable univariate scalar function

Classes in gov.sandia.cognition.math that implement DifferentiableEvaluator
 class AbstractDifferentiableUnivariateScalarFunction
          Partial implementation of DifferentiableUnivariateScalarFunction that implements the differentiate(Double) method with a callback to the differentiate(double) method, so that a concrete class only to implement the differentiate(double) method

Uses of DifferentiableEvaluator in gov.sandia.cognition.math.matrix

Subinterfaces of DifferentiableEvaluator in gov.sandia.cognition.math.matrix
 interface DifferentiableVectorFunction
          A VectorFunction that can is also differentiable
 interface VectorizableDifferentiableVectorFunction
          A VectorizableVectorFunction that also define a derivative (this is needed for GradientDescendable).

Classes in gov.sandia.cognition.math.matrix that implement DifferentiableEvaluator
 class NumericalDifferentiator<InputType,OutputType,DerivativeType>
          Automatically differentiates a function by the method of forward differences.
static class NumericalDifferentiator.DoubleJacobian
          Numerical differentiator based on a Vector Jacobian.
static class NumericalDifferentiator.MatrixJacobian
          Numerical differentiator based on a Matrix Jacobian.
static class NumericalDifferentiator.VectorJacobian
          Numerical differentiator based on a Vector Jacobian.

Uses of DifferentiableEvaluator in gov.sandia.cognition.statistics

Subinterfaces of DifferentiableEvaluator in gov.sandia.cognition.statistics
 interface SmoothCumulativeDistributionFunction
          This defines a CDF that has an associated derivative, which is its PDF.

Uses of DifferentiableEvaluator in gov.sandia.cognition.statistics.bayesian

Classes in gov.sandia.cognition.statistics.bayesian that implement DifferentiableEvaluator
static class AdaptiveRejectionSampling.LineSegment
          A line that has a minimum and maximum support (x-axis) value.

Uses of DifferentiableEvaluator in gov.sandia.cognition.statistics.distribution

Classes in gov.sandia.cognition.statistics.distribution that implement DifferentiableEvaluator
static class BetaDistribution.CDF
          CDF of the Beta-family distribution
static class CauchyDistribution.CDF
          CDF of the CauchyDistribution.
static class ChiSquareDistribution.CDF
          Cumulative Distribution Function (CDF) of a Chi-Square Distribution
static class ExponentialDistribution.CDF
          CDF of the ExponentialDistribution.
static class GammaDistribution.CDF
          CDF of the Gamma distribution
static class InverseGammaDistribution.CDF
          CDF of the inverseRootFinder-gamma distribution.
static class LaplaceDistribution.CDF
          CDF of the Laplace distribution.
static class LogisticDistribution.CDF
          CDF of the LogisticDistribution
static class LogNormalDistribution.CDF
          CDF of the Log-Normal Distribution
static class ParetoDistribution.CDF
          CDF of the Pareto Distribution.
static class ScalarMixtureDensityModel.CDF
          CDFof the SMDM
static class StudentTDistribution.CDF
          Evaluator that computes the Cumulative Distribution Function (CDF) of a Student-t distribution with a fixed number of degrees of freedom
static class UniformDistribution.CDF
          Cumulative Distribution Function of a uniform
static class UnivariateGaussian.CDF
          CDF of the underlying Gaussian.
static class WeibullDistribution.CDF
          CDF of the Weibull distribution

Uses of DifferentiableEvaluator in gov.sandia.cognition.statistics.method

Classes in gov.sandia.cognition.statistics.method that implement DifferentiableEvaluator
protected  class DistributionParameterEstimator.DistributionWrapper
          Maps the parameters of a Distribution and a CostFunction into a Vector/Double Evaluator.