| Package | Description |
|---|---|
| gov.sandia.cognition.collection |
Provides commonly useful collection implementations.
|
| gov.sandia.cognition.learning.algorithm.clustering |
Provides clustering algorithms.
|
| gov.sandia.cognition.learning.algorithm.clustering.cluster |
Provides implementations of different types of clusters.
|
| gov.sandia.cognition.learning.algorithm.clustering.divergence |
Provides divergence functions for use in clustering.
|
| gov.sandia.cognition.learning.algorithm.clustering.initializer |
Provides implementations of methods for selecting initial clusters.
|
| gov.sandia.cognition.learning.algorithm.ensemble |
Provides ensemble methods.
|
| gov.sandia.cognition.learning.algorithm.factor.machine |
Provides factorization machine algorithms.
|
| gov.sandia.cognition.learning.algorithm.minimization.line |
Provides line (scalar) minimization algorithms.
|
| gov.sandia.cognition.learning.algorithm.minimization.line.interpolator |
Provides line (scalar) interpolation/extrapolation algorithms that fit an
algebraic function to a (small) collection of data points.
|
| gov.sandia.cognition.learning.algorithm.nearest |
Provides algorithms for Nearest-Neighbor memory-based functions.
|
| gov.sandia.cognition.learning.algorithm.regression |
Provides regression algorithms, such as Linear Regression.
|
| gov.sandia.cognition.learning.algorithm.root |
Provides algorithms for finding the roots, or zero crossings, of scalar functions.
|
| gov.sandia.cognition.learning.algorithm.tree |
Provides decision tree learning algorithms.
|
| gov.sandia.cognition.learning.data.feature |
Provides data feature extractors.
|
| gov.sandia.cognition.learning.function.distance |
Provides distance functions.
|
| gov.sandia.cognition.learning.function.kernel |
Provides kernel functions.
|
| gov.sandia.cognition.learning.function.regression |
Provides functions that output real numbers from some input data structure.
|
| 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.learning.performance.categorization |
Provides performance measures for categorizers.
|
| gov.sandia.cognition.math |
Provides classes for mathematical computation.
|
| gov.sandia.cognition.math.geometry |
Provides classes and interfaces for computational geometry.
|
| gov.sandia.cognition.math.matrix |
Provides interfaces and classes for linear algebra.
|
| gov.sandia.cognition.math.matrix.custom |
Provides a custom linear algebra package implementation for both dense
and sparse classes.
|
| gov.sandia.cognition.math.matrix.decomposition |
Provides matrix decompositions.
|
| gov.sandia.cognition.math.matrix.mtj |
Provides a linear algebra package implementation wrapper using the Matrix
Toolkits for Java (MTJ) library.
|
| gov.sandia.cognition.math.matrix.mtj.decomposition |
Provides matrix decomposition implementations using the Matrix Toolkits for
Java (MTJ) library.
|
| gov.sandia.cognition.math.signals |
Provides mathematical signal processing methods.
|
| 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.
|
| gov.sandia.cognition.text.relation |
Provides classes for relationships involving text.
|
| Class and Description |
|---|
| LogNumber
Represents a number in log-space, storing the log of the absolute value
log(|value|) and the sign of the value sign(value).
|
| MutableDouble
A mutable object containing a double.
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| Metric
A metric is a non-negative function that satisfies the following properties
g(x, y) + g(y, z) >= g(x, z)
g(x, y) == g(y, x)
g(x, x) == 0.
|
| Semimetric
A semimetric is a divergence function that takes inputs from the same
set (domain) and is positive definite and symmetric.
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| Class and Description |
|---|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| Class and Description |
|---|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| Class and Description |
|---|
| 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
|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| AbstractUnivariateScalarFunction
Abstract implementation of ScalarFunction where the evaluate(Double) method
calls back into the evaluate(double) method.
|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| DifferentiableUnivariateScalarFunction
A differentiable univariate scalar function
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| DifferentiableUnivariateScalarFunction
A differentiable univariate scalar function
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| Metric
A metric is a non-negative function that satisfies the following properties
g(x, y) + g(y, z) >= g(x, z)
g(x, y) == g(y, x)
g(x, x) == 0.
|
| Class and Description |
|---|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| Class and Description |
|---|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| AbstractUnivariateScalarFunction
Abstract implementation of ScalarFunction where the evaluate(Double) method
calls back into the evaluate(double) method.
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| Class and Description |
|---|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| AbstractUnivariateScalarFunction
Abstract implementation of ScalarFunction where the evaluate(Double) method
calls back into the evaluate(double) method.
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| Metric
A metric is a non-negative function that satisfies the following properties
g(x, y) + g(y, z) >= g(x, z)
g(x, y) == g(y, x)
g(x, x) == 0.
|
| Semimetric
A semimetric is a divergence function that takes inputs from the same
set (domain) and is positive definite and symmetric.
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| Metric
A metric is a non-negative function that satisfies the following properties
g(x, y) + g(y, z) >= g(x, z)
g(x, y) == g(y, x)
g(x, x) == 0.
|
| Semimetric
A semimetric is a divergence function that takes inputs from the same
set (domain) and is positive definite and symmetric.
|
| Class and Description |
|---|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| Class and Description |
|---|
| 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
|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| AbstractUnivariateScalarFunction
Abstract implementation of ScalarFunction where the evaluate(Double) method
calls back into the evaluate(double) method.
|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| DifferentiableUnivariateScalarFunction
A differentiable univariate scalar function
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| DifferentiableUnivariateScalarFunction
A differentiable univariate scalar function
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| MutableDouble
A mutable object containing a double.
|
| Class and Description |
|---|
| AbstractEuclideanRing
An abstract implementation of the
EuclideanRing interface. |
| AbstractField
An abstract implementation of the
Field interface. |
| AbstractRing
Implements the non-inline versions of the various Ring functions.
|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| AbstractUnivariateScalarFunction
Abstract implementation of ScalarFunction where the evaluate(Double) method
calls back into the evaluate(double) method.
|
| Combinations
Enumerates all the combinations on a given number of items sampled from a
larger set without considering order, that is, (1,2) is the same as (2,1).
|
| Combinations.AbstractCombinationsIterator
Partial implementation of a CombinationsIterator.
|
| ComplexNumber
Represents a complex number in a rectangular manner, explicitly storing
the real and imaginary portions: real + j*imaginary
|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| DifferentiableUnivariateScalarFunction
A differentiable univariate scalar function
|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|
| EuclideanRing
Defines something similar to a Euclidean ring from abstract algebra.
|
| Field
Defines something similar to a mathematical field.
|
| LogNumber
Represents a number in log-space, storing the log of the absolute value
log(|value|) and the sign of the value sign(value).
|
| MutableDouble
A mutable object containing a double.
|
| MutableInteger
A mutable object containing an integer.
|
| MutableLong
A mutable object containing a long.
|
| NumberAverager
Returns an average (arithmetic mean) of a collection of Numbers
|
| Ring
Defines something similar to a mathematical ring.
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| Semimetric
A semimetric is a divergence function that takes inputs from the same
set (domain) and is positive definite and symmetric.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| UnivariateSummaryStatistics
A Bayesian-style synopsis of a Collection of scalar data.
|
| UnsignedLogNumber
Represents an unsigned number in log space, storing log(value) and operating
directly on it.
|
| WeightedNumberAverager
Averages together given set of weighted values by adding up the weight times
the value and then dividing by the total weight.
|
| Class and Description |
|---|
| Metric
A metric is a non-negative function that satisfies the following properties
g(x, y) + g(y, z) >= g(x, z)
g(x, y) == g(y, x)
g(x, x) == 0.
|
| Class and Description |
|---|
| AbstractRing
Implements the non-inline versions of the various Ring functions.
|
| ComplexNumber
Represents a complex number in a rectangular manner, explicitly storing
the real and imaginary portions: real + j*imaginary
|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| MutableDouble
A mutable object containing a double.
|
| Ring
Defines something similar to a mathematical ring.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| AbstractRing
Implements the non-inline versions of the various Ring functions.
|
| ComplexNumber
Represents a complex number in a rectangular manner, explicitly storing
the real and imaginary portions: real + j*imaginary
|
| Ring
Defines something similar to a mathematical ring.
|
| Class and Description |
|---|
| ComplexNumber
Represents a complex number in a rectangular manner, explicitly storing
the real and imaginary portions: real + j*imaginary
|
| Class and Description |
|---|
| AbstractRing
Implements the non-inline versions of the various Ring functions.
|
| ComplexNumber
Represents a complex number in a rectangular manner, explicitly storing
the real and imaginary portions: real + j*imaginary
|
| Ring
Defines something similar to a mathematical ring.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| OperationNotConvergedException
The
OperationNotConvergedException class is an exception that
is thrown when some mathematical operation does not converge, when it is
expected to converge. |
| Class and Description |
|---|
| ComplexNumber
Represents a complex number in a rectangular manner, explicitly storing
the real and imaginary portions: real + j*imaginary
|
| Class and Description |
|---|
| AbstractRing
Implements the non-inline versions of the various Ring functions.
|
| ClosedFormDifferentiableEvaluator
A differentiable function that has a closed-form derivative.
|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| MutableDouble
A mutable object containing a double.
|
| Ring
Defines something similar to a mathematical ring.
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| 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
|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| AbstractUnivariateScalarFunction
Abstract implementation of ScalarFunction where the evaluate(Double) method
calls back into the evaluate(double) method.
|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| DifferentiableUnivariateScalarFunction
A differentiable univariate scalar function
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| AbstractScalarFunction
An abstract implementation of the
ScalarFunction interface. |
| AbstractUnivariateScalarFunction
Abstract implementation of ScalarFunction where the evaluate(Double) method
calls back into the evaluate(double) method.
|
| ClosedFormDifferentiableEvaluator
A differentiable function that has a closed-form derivative.
|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| MutableDouble
A mutable object containing a double.
|
| ScalarFunction
Interface for a function that maps some input onto a double.
|
| UnivariateScalarFunction
Simple interface that describes a function that maps the reals to the reals,
has a Double to Double and double to double.
|
| Class and Description |
|---|
| DifferentiableEvaluator
Interface that indicates that the Evaluator can be differentiated about the
given input.
|
| Class and Description |
|---|
| DivergenceFunction
The DivergenceFunction class defines the functionality of something that
computes the divergence between two objects.
|