Package  Description 

gov.sandia.cognition.learning.algorithm.minimization.line 
Provides line (scalar) minimization algorithms.

gov.sandia.cognition.learning.algorithm.root 
Provides algorithms for finding the roots, or zero crossings, of scalar functions.

gov.sandia.cognition.learning.data.feature 
Provides data feature extractors.

gov.sandia.cognition.learning.function.scalar 
Provides functions that output real numbers.

gov.sandia.cognition.math 
Provides classes for mathematical computation.

gov.sandia.cognition.statistics.bayesian 
Provides algorithms for computing Bayesian estimates of parameters.

gov.sandia.cognition.statistics.distribution 
Provides statistical distributions.

Modifier and Type  Class and Description 

class 
DirectionalVectorToDifferentiableScalarFunction
Creates a truly differentiable scalar function from a differentiable Vector
function, instead of using a forwarddifferences 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 startpoint
offset.

class 
LineMinimizerDerivativeBased.InternalFunction
Internal function used to map/remap/unmap the search direction.

Modifier and Type  Class and Description 

class 
SolverFunction
Evaluator that allows RootFinders to solve for nonzero values by setting
a "target" parameter.

Modifier and Type  Class and Description 

class 
StandardDistributionNormalizer
The
StandardDistributionNormalizer class implements a normalization
method where a real value is converted onto a standard distribution. 
Modifier and Type  Class and Description 

class 
AtanFunction
Returns the elementwise arctangent of the input vector, compressed between
maxMagnitude and maxMagnitude (instead of just PI/2 and PI/2)

class 
CosineFunction
A closedform cosine function.

class 
HardSigmoidFunction
A hard sigmoid function, which is an approximation of a logistic sigmoid
whose output is between 0 and 1.

class 
HardTanHFunction
A hard sigmoid function, which is an approximation of a tanh sigmoid
whose output is between 1 and 1.

class 
IdentityScalarFunction
A univariate scalar identity function: f(x) = x.

class 
LeakyRectifiedLinearFunction
A leaky rectified linear unit.

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 realvalued 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 
RectifiedLinearFunction
A rectified linear unit, which is the maximum of its input or 0.

class 
SigmoidFunction
An implementation of a sigmoid squashing function.

class 
SoftPlusFunction
A smoothed approximation for rectified linear unit.

class 
TanHFunction
The hyperbolic tangent (tanh) function.

class 
ThresholdFunction
Maps the input space onto the set {LOW_VALUE,HIGH_VALUE}.

Modifier and Type  Class and Description 

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

Modifier and Type  Class and Description 

class 
AdaptiveRejectionSampling.AbstractEnvelope
Describes an enveloping function comprised of a sorted sequence of lines

static class 
AdaptiveRejectionSampling.LineSegment
A line that has a minimum and maximum support (xaxis) value.

static class 
AdaptiveRejectionSampling.LogEvaluator<EvaluatorType extends Evaluator<java.lang.Double,java.lang.Double>>
Wraps an Evaluator and takes the natural logarithm of the evaluate method

class 
AdaptiveRejectionSampling.LowerEnvelope
Define the lower envelope for Adaptive Rejection Sampling

static class 
AdaptiveRejectionSampling.PDFLogEvaluator
Wraps a PDF so that it returns the logEvaluate method.

class 
AdaptiveRejectionSampling.UpperEnvelope
Constructs the upper envelope for sampling.

Modifier and Type  Class and Description 

static class 
UnivariateGaussian.ErrorFunction
Gaussian Error Function, useful for computing the cumulative distribution
function for a Gaussian.

static class 
UnivariateGaussian.ErrorFunction.Inverse
Inverse of the ErrorFunction
