Package | Description |
---|---|
gov.sandia.cognition.learning.algorithm.confidence |
Provides confidence-weighted categorization algorithms.
|
gov.sandia.cognition.learning.algorithm.ensemble |
Provides ensemble methods.
|
gov.sandia.cognition.learning.algorithm.perceptron |
Provides the Perceptron algorithm and some of its variations.
|
gov.sandia.cognition.learning.algorithm.perceptron.kernel |
Modifier and Type | Class and Description |
---|---|
class |
AdaptiveRegularizationOfWeights
An implementation of the Adaptive Regularization of Weights (AROW) algorithm
for online learning of a linear binary categorizer.
|
class |
ConfidenceWeightedDiagonalDeviation
An implementation of the Standard Deviation (Stdev) algorithm for learning
a confidence-weighted categorizer.
|
class |
ConfidenceWeightedDiagonalDeviationProject
An implementation of the Standard Deviation (Stdev) algorithm for learning
a confidence-weighted categorizer.
|
class |
ConfidenceWeightedDiagonalVariance
An implementation of the Variance algorithm for learning a confidence-weighted
linear categorizer.
|
class |
ConfidenceWeightedDiagonalVarianceProject
An implementation of the Variance algorithm for learning a confidence-weighted
linear categorizer.
|
Modifier and Type | Class and Description |
---|---|
class |
OnlineBaggingCategorizerLearner<InputType,CategoryType,MemberType extends Evaluator<? super InputType,? extends CategoryType>>
An implementation of an online version of the Bagging algorithm for learning
an ensemble of categorizers.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractKernelizableBinaryCategorizerOnlineLearner
An abstract implementation of the
KernelizableBinaryCategorizerOnlineLearner
interface. |
class |
AbstractLinearCombinationOnlineLearner
An abstract class for online learning of linear binary categorizers that
take the form of a weighted sum of inputs.
|
class |
AbstractOnlineLinearBinaryCategorizerLearner
An abstract class for online (incremental) learning algorithms that produce
an
LinearBinaryCategorizer . |
class |
AggressiveRelaxedOnlineMaximumMarginAlgorithm
An implementation of the Aggressive Relaxed Online Maximum Margin Algorithm
(AROMMA).
|
class |
Ballseptron
An implementation of the Ballseptron algorithm.
|
class |
OnlineBinaryMarginInfusedRelaxedAlgorithm
An implementation of the binary MIRA algorithm.
|
class |
OnlinePassiveAggressivePerceptron
An implementation of the Passive-Aggressive algorithm for learning a linear
binary categorizer.
|
static class |
OnlinePassiveAggressivePerceptron.AbstractSoftMargin
An abstract class for soft-margin versions of the Passive-Aggressive
algorithm.
|
static class |
OnlinePassiveAggressivePerceptron.LinearSoftMargin
An implementation of the linear soft-margin variant of the Passive-
Aggressive algorithm (PA-I).
|
static class |
OnlinePassiveAggressivePerceptron.QuadraticSoftMargin
An implementation of the quadratic soft-margin variant of the Passive-
Aggressive algorithm (PA-II).
|
class |
OnlinePerceptron
An online version of the classic Perceptron algorithm.
|
class |
OnlineRampPassiveAggressivePerceptron
An implementation of the Ramp Loss Passive Aggressive Perceptron (PA^R) from
the referenced paper.
|
class |
OnlineShiftingPerceptron
An implementation of the Shifting Perceptron algorithm.
|
class |
OnlineVotedPerceptron
An online version of the Voted-Perceptron algorithm.
|
class |
RelaxedOnlineMaximumMarginAlgorithm
An implementation of the Relaxed Online Maximum Margin Algorithm
(ROMMA).
|
class |
Winnow
An implementation of the Winnow incremental learning algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
AbstractOnlineBudgetedKernelBinaryCategorizerLearner<InputType>
An abstract implementation of the
BudgetedKernelBinaryCategorizerLearner
for online learners. |
class |
AbstractOnlineKernelBinaryCategorizerLearner<InputType>
An abstract class for an online kernel binary categorizer learner.
|
class |
Forgetron<InputType>
An implementation of the "self-tuned" Forgetron algorithm, which is an online
budgeted kernel binary categorizer learner.
|
static class |
Forgetron.Basic<InputType>
An implementation of the "basic" Forgetron algorithm, which is an online
budgeted kernel binary categorizer learner.
|
static class |
Forgetron.Greedy<InputType>
An implementation of the "greedy" Forgetron algorithm, which is an online
budgeted kernel binary categorizer learner.
|
class |
KernelBinaryCategorizerOnlineLearnerAdapter<InputType>
A wrapper class for a
KernelizableBinaryCategorizerOnlineLearner
that allows it to be used as a batch or incremental learner over the
input type directly, rather than using utility methods. |
class |
OnlineKernelPerceptron<InputType>
An implementation of the online version of the Perceptron algorithm.
|
class |
OnlineKernelRandomizedBudgetPerceptron<InputType>
An implementation of a fixed-memory kernel Perceptron algorithm.
|
class |
Projectron<InputType>
An implementation of the Projectron algorithm, which is an online kernel
binary categorizer learner that has a budget parameter tuned by the eta
parameter.
|
static class |
Projectron.LinearSoftMargin<InputType>
An implementation of the Projectron++ algorithm, which is an online
kernel binary categorizer learner that has a budget parameter tuned by
the eta parameter.
|
class |
RemoveOldestKernelPerceptron<InputType>
A budget kernel Perceptron that always removes the oldest item.
|
class |
Stoptron<InputType>
An online, budgeted, kernel version of the Perceptron algorithm that stops
learning once it has reached its budget.
|