Package | Description |
---|---|
gov.sandia.cognition.algorithm |
Provides general interfaces and implementations for algorithms.
|
gov.sandia.cognition.algorithm.event |
Provides useful components for handling algorithm events.
|
gov.sandia.cognition.learning.algorithm.clustering |
Provides clustering algorithms.
|
gov.sandia.cognition.learning.algorithm.ensemble |
Provides ensemble methods.
|
gov.sandia.cognition.learning.algorithm.minimization.matrix |
Provides matrix solving algorithms.
|
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.function.vector |
Provides functions that output vectors.
|
gov.sandia.cognition.learning.performance |
Provides performance measures.
|
gov.sandia.cognition.statistics.distribution |
Provides statistical distributions.
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gov.sandia.cognition.statistics.method |
Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods.
|
gov.sandia.cognition.text.topic |
Provides topic modeling algorithms.
|
Modifier and Type | Class and Description |
---|---|
class |
AnytimeAlgorithmWrapper<ResultType,InternalAlgorithm extends AnytimeAlgorithm<?>>
Wraps an AnytimeAlgorithm.
|
Modifier and Type | Method and Description |
---|---|
protected java.util.LinkedList<IterativeAlgorithmListener> |
AbstractIterativeAlgorithm.getListeners()
Retrieves the list of listeners for this algorithm.
|
Modifier and Type | Method and Description |
---|---|
void |
AbstractIterativeAlgorithm.addIterativeAlgorithmListener(IterativeAlgorithmListener listener) |
void |
IterativeAlgorithm.addIterativeAlgorithmListener(IterativeAlgorithmListener listener)
Adds a listener for the iterations of the algorithm.
|
void |
AbstractIterativeAlgorithm.removeIterativeAlgorithmListener(IterativeAlgorithmListener listener) |
void |
IterativeAlgorithm.removeIterativeAlgorithmListener(IterativeAlgorithmListener listener)
Removes a listener for the iterations of the algorithm.
|
Modifier and Type | Method and Description |
---|---|
protected void |
AbstractIterativeAlgorithm.setListeners(java.util.LinkedList<IterativeAlgorithmListener> listeners)
Sets the list of listeners for this algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractIterativeAlgorithmListener
An abstract implementation of the
IterativeAlgorithmListener
interface that provides default implementations of the event methods that
do nothing. |
class |
IterationMeasurablePerformanceReporter
An iterative algorithm listeners for
MeasurablePerformanceAlgorithm
objects that reports the performance of the algorithm at the end of each
iteration. |
class |
IterationStartReporter
An iterative algorithm listener that reports the start of each iteration
to the given print stream.
|
Modifier and Type | Class and Description |
---|---|
class |
DirichletProcessClustering
Clustering algorithm that wraps Dirichlet Process Mixture Model.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractCategorizerOutOfBagStoppingCriteria<InputType,CategoryType>
Abstract class for implementing a out-of-bag stopping criteria for a
bagging-based ensemble.
|
static class |
BaggingCategorizerLearner.OutOfBagErrorStoppingCriteria<InputType,CategoryType>
Implements a stopping criteria for bagging that uses the out-of-bag
error to determine when to stop learning the ensemble.
|
static class |
IVotingCategorizerLearner.OutOfBagErrorStoppingCriteria<InputType,CategoryType>
Implements a stopping criteria for IVoting that uses the out-of-bag
error to determine when to stop learning the ensemble.
|
Modifier and Type | Field and Description |
---|---|
protected java.util.Set<IterativeAlgorithmListener> |
IterativeMatrixSolver.listeners
Listeners to the algorithms progress have the opportunity to stop the
algorithm after a specified number of iterations.
|
Modifier and Type | Method and Description |
---|---|
void |
IterativeMatrixSolver.addIterativeAlgorithmListener(IterativeAlgorithmListener listener) |
void |
IterativeMatrixSolver.removeIterativeAlgorithmListener(IterativeAlgorithmListener listener) |
Modifier and Type | Class and Description |
---|---|
class |
AbstractMinimizerBasedParameterCostMinimizer<ResultType extends VectorizableVectorFunction,EvaluatorType extends Evaluator<? super Vector,? extends java.lang.Double>>
Partial implementation of ParameterCostMinimizer, based on the algorithms
from the minimization package.
|
class |
ParameterDerivativeFreeCostMinimizer
Implementation of a class of objects that uses a derivative-free
minimization algorithm.
|
class |
ParameterDifferentiableCostMinimizer
This class adapts the unconstrained nonlinear minimization algorithms in
the "minimization" package to the task of estimating locally optimal
(minimum-cost) parameter sets.
|
Modifier and Type | Class and Description |
---|---|
class |
MinimizerBasedRootFinder
A root finder that uses minimization techniques to find the roots
(zero-crossings).
|
Modifier and Type | Class and Description |
---|---|
static class |
GaussianContextRecognizer.Learner
Creates a GaussianContextRecognizer from a Dataset[Vector] using
a BatchClusterer
|
Modifier and Type | Class and Description |
---|---|
class |
AnytimeBatchLearnerValidationPerformanceReporter<DataType,ObjectType>
A performance reporter for a validation set.
|
Modifier and Type | Class and Description |
---|---|
static class |
MixtureOfGaussians.Learner
A hard-assignment learner for a MixtureOfGaussians
|
Modifier and Type | Class and Description |
---|---|
class |
DistributionParameterEstimator<DataType,DistributionType extends ClosedFormDistribution<? extends DataType>>
A method of estimating the parameters of a distribution using an arbitrary
CostFunction and FunctionMinimizer algorithm.
|
Modifier and Type | Class and Description |
---|---|
static class |
ProbabilisticLatentSemanticAnalysis.StatusPrinter
Prints out the status of the probabilistic latent semantic analysis
algorithm.
|