Uses of Class
gov.sandia.cognition.annotation.CodeReview

Packages that use CodeReview

Package	Description
gov.sandia.cognition.algorithm	Provides general interfaces and implementations for algorithms.
gov.sandia.cognition.annotation	Provides commonly useful annotations.
gov.sandia.cognition.collection	Provides commonly useful collection implementations.
gov.sandia.cognition.evaluator	Provides interfaces and classes to do with the Evaluator interface.
gov.sandia.cognition.factory	Provides interfaces and implementations of general factory objects.
gov.sandia.cognition.io	Provides general classes for assisting with input/output operations.
gov.sandia.cognition.learning.algorithm	Provides general interfaces for learning algorithms.
gov.sandia.cognition.learning.algorithm.baseline	Provides baseline (dummy) learning algorithms.
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.gradient	Provides gradient based learning algorithms.
gov.sandia.cognition.learning.algorithm.minimization.line	Provides line (scalar) minimization algorithms.
gov.sandia.cognition.learning.algorithm.pca	Provides implementations of Principle Components Analysis (PCA).
gov.sandia.cognition.learning.algorithm.perceptron	Provides the Perceptron algorithm and some of its variations.
gov.sandia.cognition.learning.algorithm.perceptron.kernel
gov.sandia.cognition.learning.algorithm.regression	Provides regression algorithms, such as Linear Regression.
gov.sandia.cognition.learning.algorithm.svm	Provides implementations of Support Vector Machine (SVM) learning algorithms.
gov.sandia.cognition.learning.data	Provides data set utilities for learning.
gov.sandia.cognition.learning.data.feature	Provides data feature extractors.
gov.sandia.cognition.learning.function.cost	Provides cost functions.
gov.sandia.cognition.learning.function.kernel	Provides kernel functions.
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.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.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.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.util	Provides general utility classes.

Uses of CodeReview in gov.sandia.cognition.algorithm

Classes in gov.sandia.cognition.algorithm with annotations of type CodeReview

Modifier and Type	Class and Description
class	AbstractAnytimeAlgorithm<ResultType> A partial implementation of the common functionality of an AnytimeAlgorithm.
interface	AnytimeAlgorithm<ResultType> The AnytimeAlgorithm interface defines the functionality of an iterative algorithm that is stoppable and can return intermediate results.
interface	MeasurablePerformanceAlgorithm An interface for an algorithm that has a measurable quantity of performance that can be retrieved.

Uses of CodeReview in gov.sandia.cognition.annotation

Classes in gov.sandia.cognition.annotation with annotations of type CodeReview

Modifier and Type	Class and Description
interface	CodeReview The CodeReview annotation describes information about the last code review for a piece of code.
interface	CodeReviewResponse The CodeReviewResponse annotation contains information regarding a response to a CodeReview annotation.
interface	CodeReviews The CodeReviews annotation defines a container for one or more CodeReview annotations.
interface	Documentation The Documentation annotation marks that something is just documentation.
interface	ModelingApproximation The ModelingApproximation annotation indicates that an approximation is being used in modeling a component.
interface	PublicationReference The PublicationReference annotation describes a reference to a publication from a journal, conference, etc.
interface	PublicationReferences The PublicationReferences annotation defines a container for one or more references to a publication.
class	PublicationType The PublicationType enumeration lists off the possible types of publications for a PublicationReference annotation.
interface	SoftwareReference Describes a reference to software.
interface	SoftwareReferences The SoftwareReferences annotation defines a container for one or more references to a publication.

Uses of CodeReview in gov.sandia.cognition.collection

Classes in gov.sandia.cognition.collection with annotations of type CodeReview

Modifier and Type	Class and Description
class	CollectionUtil The CollectionUtil class implements static methods for dealing with Collection and Iterable objects.
class	DefaultComparator<T extends java.lang.Comparable<? super T>> A default comparator that just calls compare on the comparable generic it uses.
class	FiniteCapacityBuffer<DataType> A finite capacity buffer backed by a fixed array.
class	RangeExcludedArrayList<E> The RangeExcludedArrayList class implements a light-weight list on top of an ArrayList where a certain range of values is excluded from the list.

Uses of CodeReview in gov.sandia.cognition.evaluator

Classes in gov.sandia.cognition.evaluator with annotations of type CodeReview

Modifier and Type	Class and Description
class	CompositeEvaluatorPair<InputType,IntermediateType,OutputType> Implements a composition of two evaluators.
class	CompositeEvaluatorTriple<InputType,FirstIntermediateType,SecondIntermediateType,OutputType> Implements a composition of three evaluators.
interface	StatefulEvaluator<InputType,OutputType,StateType extends CloneableSerializable> The StatefulEvaluator interface defines the functionality of an Evaluator that maintains an internal state.
class	ValueClamper<DataType extends java.lang.Comparable<DataType>> An evaluator that clamps a number between minimum and maximum values.
class	ValueMapper<InputType,OutputType> An evaluator that uses a map to map input values to their appropriate output values.

Uses of CodeReview in gov.sandia.cognition.factory

Classes in gov.sandia.cognition.factory with annotations of type CodeReview

Modifier and Type	Class and Description
class	ConstructorBasedFactory<CreatedType> The ConstructorBasedFactory class implements a Factory that takes a constructor and parameters to that constructor used to create new objects.
class	DefaultFactory<CreatedType> The DefaultFactory class is a default implementation of the Factory interface that takes a class as its parameter and uses the default constructor of the class, called through newInstance(), to create new objects of that class.
interface	Factory<CreatedType> The Factory interface defines a very general interface for a factory object that can be used to create some other type of object.
class	PrototypeFactory<CreatedType extends CloneableSerializable> The PrototypeFactory class implements a Factory that uses a prototype object to create new objects from by cloning it.

Uses of CodeReview in gov.sandia.cognition.io

Classes in gov.sandia.cognition.io with annotations of type CodeReview

Modifier and Type	Class and Description
class	FileUtil The FileUtil class defines some useful utilities for dealing with files.
class	ReaderTokenizer Reads each line from a Reader, and returns each line as a List of Strings

Uses of CodeReview in gov.sandia.cognition.learning.algorithm

Classes in gov.sandia.cognition.learning.algorithm with annotations of type CodeReview

Modifier and Type	Class and Description
class	AbstractAnytimeBatchLearner<DataType,ResultType> The AbstractAnytimeBatchLearner abstract class implements a standard method for conforming to the BatchLearner and AnytimeLearner (IterativeAlgorithm and StoppableAlgorithm) interfaces.
class	AbstractAnytimeSupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> The AbstractAnytimeSupervisedBatchLearner abstract class extends the AbstractAnytimeBatchLearner to implement the SupervisedBatchLearner interface.
interface	BatchLearner<DataType,ResultType> The BatchLearner interface defines the general functionality of an object that is the implementation of a data-driven, batch machine learning algorithm.
interface	IncrementalLearner<DataType,ResultType> The IncrementalLearner interface defines the general functionality of an object that is the implementation of a data-driven, incremental machine learning algorithm.
interface	SupervisedBatchLearner<InputType,OutputType,ResultType extends Evaluator<? super InputType,? extends OutputType>> The BatchSupervisedLearner interface is an extension of the BatchLearner interface that contains the typical generic definition conventions for a batch, supervised learning algorithm.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.baseline

Classes in gov.sandia.cognition.learning.algorithm.baseline with annotations of type CodeReview

Modifier and Type	Class and Description
class	MeanLearner The MeanLearner class implements a baseline learner that computes the mean of a given set of values.
class	MostFrequentLearner<OutputType> The MostFrequentLearner class implements a baseline learner that computes the most frequent output value.
class	WeightedMeanLearner The WeightedMeanLearner class implements a baseline learner that computes the weighted mean output value.
class	WeightedMostFrequentLearner<OutputType> The WeightedMostFrequentLearner class implements a baseline learning algorithm that finds the most frequent output of a given dataset based on the weights of the examples.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.clustering

Classes in gov.sandia.cognition.learning.algorithm.clustering with annotations of type CodeReview

Modifier and Type	Class and Description
class	AffinityPropagation<DataType> The AffinityPropagation algorithm requires three parameters: a divergence function, a value to use for self-divergence, and a damping factor (called lambda in the paper; 0.5 is the default).
class	AgglomerativeClusterer<DataType,ClusterType extends Cluster<DataType>> The AgglomerativeClusterer implements an agglomerative clustering algorithm, which is a type of hierarchical clustering algorithm.
interface	BatchClusterer<DataType,ClusterType extends Cluster<DataType>> The BatchClusterer interface defines the functionality of a batch clustering algorithm.
class	KMeansClustererWithRemoval<DataType,ClusterType extends Cluster<DataType>> Creates a k-means clustering algorithm that removes clusters that do not have sufficient membership to pass a simple statistical significance test.
class	KMeansFactory Creates a parallelized version of the k-means clustering algorithm for the typical use: clustering vector data with a Euclidean distance metric.
class	OptimizedKMeansClusterer<DataType> This class implements an optimized version of the k-means algorithm that makes use of the triangle inequality to compute the same answer as k-means while using less distance calculations.
class	PartitionalClusterer<DataType,ClusterType extends Cluster<DataType>> The PartitionalClusterer implements a partitional clustering algorithm, which is a type of hierarchical clustering algorithm.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.clustering.cluster

Classes in gov.sandia.cognition.learning.algorithm.clustering.cluster with annotations of type CodeReview

Modifier and Type	Class and Description
class	CentroidCluster<ClusterType> The CentroidCluster class extends the default cluster to contain a central element.
interface	Cluster<ClusterType> The Cluster interface defines the general functionality of a cluster, which is just the ability to get the members of the cluster.
interface	ClusterCreator<ClusterType extends Cluster<DataType>,DataType> The ClusterCreator defines the functionality of a class that can create a new cluster from a given collection of members of that cluster.
class	DefaultCluster<ClusterType> The DefaultCluster class implements a default cluster which contains a list of members in an ArrayList along with an index that identifies the cluster.
class	GaussianCluster The GaussianCluster class implements a cluster of Vector objects that has a MultivariateGaussian object representing the cluster.
class	GaussianClusterCreator The GaussianClusterCreator class implements a ClusterCreator for creating GaussianClusters by fitting a MultivariateGaussian to the given set of example vectors.
class	MedoidClusterCreator<DataType> The MedoidClusterCreator class creates a CentroidCluster at the sample that minimizes the sum of the divergence to the objects assigned to the cluster.
class	VectorMeanCentroidClusterCreator The VectorMeanCentroidClusterCreator class implements a cluster creator for centroid clusters where the centroid is the mean of the vectors that are members of the cluster.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.clustering.divergence

Classes in gov.sandia.cognition.learning.algorithm.clustering.divergence with annotations of type CodeReview

Modifier and Type	Class and Description
class	AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The AbstractClusterToClusterDivergenceFunction class is an abstract class that helps out implementations of ClusterToClusterDivergenceFunction implementations by holding a DivergenceFunction between elements of a cluster.
class	CentroidClusterDivergenceFunction<DataType> The CentroidClusterDivergenceFunction class implements a divergence function between a cluster and an object by computing the divergence between the center of the cluster and the object.
class	ClusterCentroidDivergenceFunction<DataType> The ClusterCentroidDivergenceFunction class implements the distance between two clusters by computing the distance between the cluster's centroid.
class	ClusterCompleteLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterCompleteLinkDivergenceFunction class implements the complete linkage distance metric between two clusters.
interface	ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterDivergenceFunction interface defines a function that computes the divergence between a cluster and some other object.
class	ClusterMeanLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterMeanLinkDivergenceFunction class implements the mean linkage distance metric between two clusters.
class	ClusterSingleLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterSingleLinkDivergenceFunction class implements the complete linkage distance metric between two clusters.
interface	ClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterToClusterDivergenceFunction defines a DivergenceFunction between two clusters of the same data type.
class	GaussianClusterDivergenceFunction The GaussianClusterDivergenceFunction class implements a divergence function between a Gaussian cluster and a vector, which is calculated by finding the likelihood that the vector was generated from that Gaussian and then returning the negative of the likelihood since it is a divergence measure, not a similarity measure.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.clustering.initializer

Classes in gov.sandia.cognition.learning.algorithm.clustering.initializer with annotations of type CodeReview

Modifier and Type	Interface and Description
interface	FixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> The FixedClusterInitializer interface defines the functionality of a class that can initialize a given number of clusters from a set of elements.
class	GreedyClusterInitializer<ClusterType extends Cluster<DataType>,DataType> Implements a FixedClusterInitializer that greedily attempts to create the initial clusters.
class	NeighborhoodGaussianClusterInitializer Creates GaussianClusters near existing, but not on top of, data points.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.ensemble

Classes in gov.sandia.cognition.learning.algorithm.ensemble with annotations of type CodeReview

Modifier and Type	Class and Description
class	AdaBoost<InputType> The AdaBoost class implements the Adaptive Boosting (AdaBoost) algorithm formulated by Yoav Freund and Robert Shapire.
class	BinaryBaggingLearner<InputType> The BinaryBaggingLearner implements the Bagging learning algorithm.
class	BinaryCategorizerSelector<InputType> The BinaryCategorizerSelector class implements a "weak learner" meant for use in boosting algorithms that selects the best BinaryCategorizer from a pre-set list by picking the one with the best weighted error.
interface	Ensemble<MemberType> The Ensemble interface defines the functionality of an "ensemble" that is typically created by combining together the result of multiple learning algorithms.
class	WeightedBinaryEnsemble<InputType,MemberType extends Evaluator<? super InputType,? extends java.lang.Boolean>> The WeightedBinaryEnsemble class implements an Ensemble of BinaryCategorizer objects where each categorizer is assigned a weight and the category is selected by choosing the one with the largest sum of weights.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.gradient

Classes in gov.sandia.cognition.learning.algorithm.gradient with annotations of type CodeReview

Modifier and Type	Class and Description
class	GradientDescendableApproximator Creates a radientDescendable from a VectorizableVectorFunction by estimating the parameter gradient using a forward-difference approximation of the parameter Jacobian.
interface	ParameterGradientEvaluator<InputType,OutputType,GradientType> Interface for computing the derivative of the output with respect to the parameters for a given input.

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

Classes in gov.sandia.cognition.learning.algorithm.minimization.line with annotations of type CodeReview

Modifier and Type	Class and Description
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.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.pca

Classes in gov.sandia.cognition.learning.algorithm.pca with annotations of type CodeReview

Modifier and Type	Class and Description
class	AbstractPrincipalComponentsAnalysis Abstract implementation of PCA.
class	GeneralizedHebbianAlgorithm Implementation of the Generalized Hebbian Algorithm, also known as Sanger's Rule, which is a generalization of Oja's Rule.
interface	PrincipalComponentsAnalysis Principal Components Analysis is a family of algorithms that map from a high-dimensional input space to a low-dimensional output space.
class	PrincipalComponentsAnalysisFunction This VectorFunction maps a high-dimension input space onto a (hopefully) simple low-dimensional output space by subtracting the mean of the input data, and passing the zero-mean input through a dimension-reducing matrix multiplication function.
class	ThinSingularValueDecomposition Computes the "thin" singular value decomposition of a dataset.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.perceptron

Classes in gov.sandia.cognition.learning.algorithm.perceptron with annotations of type CodeReview

Modifier and Type	Class and Description
class	Perceptron The Perceptron class implements the standard Perceptron learning algorithm that learns a binary classifier based on vector input.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.perceptron.kernel

Classes in gov.sandia.cognition.learning.algorithm.perceptron.kernel with annotations of type CodeReview

Modifier and Type	Class and Description
class	KernelAdatron<InputType> The KernelAdatron class implements an online version of the Support Vector Machine learning algorithm.
class	KernelPerceptron<InputType> The KernelPerceptron class implements the kernel version of the Perceptron algorithm.

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

Classes in gov.sandia.cognition.learning.algorithm.regression with annotations of type CodeReview

Modifier and Type	Class and Description
class	LinearBasisRegression<InputType> Computes the least-squares regression for a LinearCombinationFunction given a dataset.
class	LinearRegression Computes the least-squares regression for a LinearCombinationFunction given a dataset.

Uses of CodeReview in gov.sandia.cognition.learning.algorithm.svm

Classes in gov.sandia.cognition.learning.algorithm.svm with annotations of type CodeReview

Modifier and Type	Class and Description
class	SuccessiveOverrelaxation<InputType> The SuccessiveOverrelaxation class implements the Successive Overrelaxation (SOR) algorithm for learning a Support Vector Machine (SVM).

Uses of CodeReview in gov.sandia.cognition.learning.data

Classes in gov.sandia.cognition.learning.data with annotations of type CodeReview

Modifier and Type	Interface and Description
interface	InputOutputPair<InputType,OutputType> The InputOutputPair interface is just a container for an input and its associated output used in supervised learning.
interface	WeightedInputOutputPair<InputType,OutputType> The WeightedInputOutputPair class implements an additional weighting term on an InputOutputPair, typically used to inform learning algorithms of the relative weight between examples.

Uses of CodeReview in gov.sandia.cognition.learning.data.feature

Classes in gov.sandia.cognition.learning.data.feature with annotations of type CodeReview

Modifier and Type	Class and Description
class	LinearRegressionCoefficientExtractor Takes a sampled sequence of equal-dimension vectors as input and computes the linear regression coefficients for each dimension in the vectors.
class	StandardDistributionNormalizer The StandardDistributionNormalizer class implements a normalization method where a real value is converted onto a standard distribution.

Uses of CodeReview in gov.sandia.cognition.learning.function.cost

Classes in gov.sandia.cognition.learning.function.cost with annotations of type CodeReview

Modifier and Type	Interface and Description
interface	CostFunction<EvaluatedType,CostParametersType> The CostFunction interface defines the interface to evaluate some object to determine its cost.
class	EuclideanDistanceCostFunction The EuclideanDistanceCostFunction class implements a CostFunction that calculates the Euclidean distance the given Vectorizable and the goal vector.
class	MeanSquaredErrorCostFunction The MeanSquaredErrorCostFunction implements a cost function for functions that take as input a vector and return a vector.

Uses of CodeReview in gov.sandia.cognition.learning.function.kernel

Classes in gov.sandia.cognition.learning.function.kernel with annotations of type CodeReview

Modifier and Type	Class and Description
class	DefaultKernelContainer<InputType> The DefaultKernelContainer class implements an object that contains a kernel inside.
class	DefaultKernelsContainer<InputType> The DefaultKernelsContainer class implements a container of kernels.
class	ExponentialKernel<InputType> The ExponentialKernel class implements a kernel that applies the exponential function to the result of another kernel.
interface	Kernel<InputType> The Kernel interface the functionality required from an object that implements a kernel function.
interface	KernelContainer<InputType> Defines an object that contains a Kernel.
class	KernelDistanceMetric<InputType> The KernelDistanceMetric class implements a distance metric that utilizes an underlying Kernel for computing the distance.
class	LinearKernel The LinearKernel class implements the most basic kernel: it just does the actual inner product between two vectors.
class	NormalizedKernel<InputType> The NormalizedKernel class implements an Kernel that returns a normalized value between 0.0 and 1.0 by normalizing the results of a given kernel.
class	PolynomialKernel The PolynomialKernel class implements a kernel for two given vectors that is the polynomial function: (x dot y + c)^d d is the degree of the polynomial, which must be a positive integer.
class	ProductKernel<InputType> The ProductKernel class implements a kernel that takes the product of applying multiple kernels to the same pair of inputs.
class	RadialBasisKernel The RadialBasisKernel implements the standard radial basis kernel, which is: exp( -||x - y||^2 / (2 * sigma^2) ) where sigma is the parameter that controls the bandwidth of the kernel.
class	ScalarFunctionKernel<InputType> The ScalarFunctionKernel class implements a kernel that applies a scalar function two the two inputs to the kernel and then returns their product.
class	SigmoidKernel The SigmoidKernel class implements a sigmoid kernel based on the hyperbolic tangent.
class	SumKernel<InputType> The SumKernel class implements a kernel that adds together the result of applying multiple kernels to the same pair of inputs.
class	VectorFunctionKernel The VectorFunctionKernel implements a kernel that makes use of a vector function plus a kernel that operates on vectors.
class	WeightedKernel<InputType> The WeightedKernel class implements a kernel that takes another kernel, evaluates it, and then the result is rescaled by a given weight.
class	ZeroKernel The ZeroKernel always returns zero.

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

Classes in gov.sandia.cognition.learning.function.scalar with annotations of type CodeReview

Modifier and Type	Class and Description
class	LinearVectorScalarFunction The LinearVectorScalarFunction class implements a scalar function that is implemented by a linear function.
class	VectorFunctionToScalarFunction<InputType> The VectorFunctionToScalarFunction class implements an adapter for using a vector function that outputs a single-dimensional vector as a scalar function.

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

Classes in gov.sandia.cognition.learning.function.vector with annotations of type CodeReview

Modifier and Type	Class and Description
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.

Uses of CodeReview in gov.sandia.cognition.math

Classes in gov.sandia.cognition.math with annotations of type CodeReview

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
interface	DifferentiableEvaluator<InputType,OutputType,DerivativeType> Interface that indicates that the Evaluator can be differentiated about the given input.
interface	DifferentiableUnivariateScalarFunction A differentiable univariate scalar function
class	MathUtil The MathUtil class implements mathematical utility functions.
class	NumberAverager Returns an average (arithmetic mean) of a collection of Numbers
class	Permutation The Permutation class contains methods for dealing with permutations of object sets.
class	RingAverager<RingType extends Ring<RingType>> A type of Averager for Rings (Matrices, Vectors, ComplexNumbers).
interface	UnivariateScalarFunction Simple interface that describes a function that maps the reals to the reals, has a Double to Double and double to double.

Uses of CodeReview in gov.sandia.cognition.math.geometry

Classes in gov.sandia.cognition.math.geometry with annotations of type CodeReview

Modifier and Type	Class and Description
class	Quadtree<DataType extends Vectorizable> Implements the quadtree region-partitioning algorithm and data structure.

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

Classes in gov.sandia.cognition.math.matrix with annotations of type CodeReview

Modifier and Type	Class and Description
class	DefaultTwoVectorEntry Stores an entry for two vectors.
interface	DifferentiableVectorFunction A VectorFunction that can is also differentiable
class	DimensionalityMismatchException Gets thrown when the dimensions don't agree for a matrix/vector operation
interface	MatrixEntry Interface that specifies the functionality for a matrix entry
class	MatrixReader Reads a Matrix from the specified reader.
class	MatrixUnionIterator Iterator that stops at all nonzero entries for EITHER underlying matrix
class	MatrixWriter Writes a Matrix to a Java-based Writer (files, etc.)
interface	TwoMatrixEntry Interface that specifies the functionality for a class that stores entries for two matrices
interface	TwoVectorEntry Interface that specifies the functionality for a class that stores entries for two vectors
interface	VectorEntry Interface the specifies the functionality that a VectorEntry should have
interface	VectorFunction A vector function is a type of Evaluator that takes a Vector for its input and output.
interface	Vectorizable The Vectorizable interface is an interface for an object that can be converted to and from a Vector.
interface	VectorizableDifferentiableVectorFunction A VectorizableVectorFunction that also define a derivative (this is needed for GradientDescendable).
interface	VectorizableVectorFunction The VectorizableVectorFunction interface defines a useful interface for doing machine learning, which is a function that takes and returns vectors and also is parameterizable as a vector.
class	VectorReader Reads a Vector from a single line in a file
class	VectorUnionIterator Iterator that returns all nonzero entries for either underlying Vector
class	VectorWriter Writes a Vector to a Java-based Writer (files, etc.)

Uses of CodeReview in gov.sandia.cognition.math.matrix.decomposition

Classes in gov.sandia.cognition.math.matrix.decomposition with annotations of type CodeReview

Modifier and Type	Class and Description
class	AbstractEigenDecomposition Abstract partial implementation of the EigenDecomposition interface
class	AbstractSingularValueDecomposition Abstract container class that stores the matrices for a Singular Value Decomposition (SVD) and related operations but does not actually perform a singular value decomposition
interface	EigenDecomposition Performs a right eigendecomposition for symmetric or asymmetric matrices
interface	SingularValueDecomposition Interface that describes the operations of all SingularValueDecompositions

Uses of CodeReview in gov.sandia.cognition.math.matrix.mtj

Classes in gov.sandia.cognition.math.matrix.mtj with annotations of type CodeReview

Modifier and Type	Class and Description
class	AbstractMTJMatrix Relies on internal MTJ matrix to do some of the heavy lifting, without assuming that the underlying matrix is Dense or Sparse
class	AbstractMTJVector Implementation of the Vector interface that relies on MTJ Vectors, but does not specify sparse or dense storage.
class	AbstractSparseMatrix Implements some generic operations that any sparse-matrix representation must do.
class	DenseMatrix Matrix that represents all its entries using a fixed-size storage scheme, based on MTJ's DenseMatrix storage class.
class	DenseVector A generally useful vector representation that allocates a fixed-size underlying vector, based on MTJ's DenseVector
class	SparseColumnMatrix A sparse matrix, represented as a collection of sparse column vectors.
class	SparseMatrix A sparse matrix, represented as a collection of sparse row vectors.
class	SparseRowMatrix A sparse matrix, represented as a collection of sparse row vectors.
class	SparseVector A vector that only stores the nonzero elements, relies on MTJ's SparseVector.
class	Vector2 Implements a two-dimensional MTJ DenseVector.
class	Vector3 Implements a three-dimensional DenseVector.

Uses of CodeReview in gov.sandia.cognition.math.matrix.mtj.decomposition

Classes in gov.sandia.cognition.math.matrix.mtj.decomposition with annotations of type CodeReview

Modifier and Type	Class and Description
class	SingularValueDecompositionMTJ Full singular-value decomposition, based on MTJ's SVD.

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

Classes in gov.sandia.cognition.statistics.distribution with annotations of type CodeReview

Modifier and Type	Class and Description
class	DataCountTreeSetBinnedMapHistogram<ValueType extends java.lang.Comparable<? super ValueType>> The DataCountTreeSetBinnedMapHistogram class extends a DefaultDataDistribution by mapping values to user defined bins using a TreeSetBinner.
class	MultivariateGaussian The MultivariateGaussian class implements a multidimensional Gaussian distribution that contains a mean vector and a covariance matrix.
class	ScalarMixtureDensityModel ScalarMixtureDensityModel (SMDM) implements just that: a scalar mixture density model.

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

Classes in gov.sandia.cognition.statistics.method with annotations of type CodeReview

Modifier and Type	Interface and Description
interface	Binner<ValueType,BinnedType> Defines the functionality for a class that assigns values to some sort of bin.
class	TreeSetBinner<ValueType extends java.lang.Comparable<? super ValueType>> Implements a Binner that employs a TreeSet to define the boundaries of a contiguous set of bins.

Uses of CodeReview in gov.sandia.cognition.util

Classes in gov.sandia.cognition.util with annotations of type CodeReview

Modifier and Type	Class and Description
class	AbstractNamed The AbstractNamed class implements the Named interface in a standard way by having a name field inside the object.
class	AbstractWeighted Container class for a Weighted object
class	DefaultWeightedValue<ValueType> The WeightedValue class implements a simple generic container that holds a value and a weight assigned to the value.