Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES

## Uses of Interface
cc.mallet.optimize.Optimizable.ByGradientValue

Packages that use Optimizable.ByGradientValue
cc.mallet.classify | Classes for training and classifying instances.
cc.mallet.fst | Transducers, including Conditional Random Fields (CRFs).
cc.mallet.fst.semi_supervised |
cc.mallet.grmm.learning |
cc.mallet.optimize | Classes for finding the maximum of a function.
cc.mallet.optimize.tests | JUnit tests for maximize.
cc.mallet.topics |

Uses of Optimizable.ByGradientValue in cc.mallet.classify

Classes in cc.mallet.classify that implement Optimizable.ByGradientValue
`class` | `MaxEntOptimizableByGE`
`class` | `MaxEntOptimizableByLabelDistribution`
`class` | `MaxEntOptimizableByLabelLikelihood`

Methods in cc.mallet.classify that return Optimizable.ByGradientValue
`Optimizable.ByGradientValue` | `RankMaxEntTrainer.getMaximizableTrainer(InstanceList ilist)`
`Optimizable.ByGradientValue` | `MCMaxEntTrainer.getMaximizableTrainer(InstanceList ilist)`

Uses of Optimizable.ByGradientValue in cc.mallet.fst

Classes in cc.mallet.fst that implement Optimizable.ByGradientValue
`class` | `CRFOptimizableByGradientValues` A CRF objective function that is the sum of multiple objective functions that implement Optimizable.ByGradientValue.
`class` | `CRFOptimizableByLabelLikelihood` An objective function for CRFs that is the label likelihood plus a Gaussian or hyperbolic prior on parameters.
`class` | `CRFTrainerByValueGradients.OptimizableCRF` An optimizable CRF that contains a collection of objective functions.
`class` | `MEMMTrainer.MEMMOptimizableByLabelLikelihood` Represents the terms in the objective function.
`class` | `ThreadedOptimizable` An adaptor for optimizables based on batch values/gradients.

Methods in cc.mallet.fst that return Optimizable.ByGradientValue
`Optimizable.ByGradientValue[]` | `CRFTrainerByValueGradients.getOptimizableByGradientValueObjects()`
`Optimizable.ByGradientValue` | `CRFOptimizableByLabelLikelihood.Factory.newCRFOptimizable(CRF crf, InstanceList trainingData)`

Constructors in cc.mallet.fst with parameters of type Optimizable.ByGradientValue
`CRFOptimizableByGradientValues(CRF crf, Optimizable.ByGradientValue[] opts)`
`CRFTrainerByValueGradients(CRF crf, Optimizable.ByGradientValue[] optimizableByValueGradientObjects)`

Uses of Optimizable.ByGradientValue in cc.mallet.fst.semi_supervised

Classes in cc.mallet.fst.semi_supervised that implement Optimizable.ByGradientValue
`class` | `CRFOptimizableByEntropyRegularization` A CRF objective function that is the entropy of the CRF's predictions on unlabeled data.
`class` | `CRFOptimizableByGECriteria` GE criteria for training a linear chain CRF.

Uses of Optimizable.ByGradientValue in cc.mallet.grmm.learning

Classes in cc.mallet.grmm.learning that implement Optimizable.ByGradientValue
`class` | `ACRF.MaximizableACRF`

Methods in cc.mallet.grmm.learning that return Optimizable.ByGradientValue
`protected Optimizable.ByGradientValue` | `DefaultAcrfTrainer.createMaximizable(ACRF acrf, InstanceList trainingList)`
`Optimizable.ByGradientValue` | `ACRF.getMaximizable(InstanceList ilst)`

Methods in cc.mallet.grmm.learning with parameters of type Optimizable.ByGradientValue
`boolean` | `DefaultAcrfTrainer.train(ACRF acrf, InstanceList trainingList, InstanceList validationList, InstanceList testSet, ACRFEvaluator eval, int numIter, Optimizable.ByGradientValue macrf)`
`boolean` | `ACRFTrainer.train(ACRF acrf, InstanceList training, InstanceList validation, InstanceList testing, ACRFEvaluator eval, int numIter, Optimizable.ByGradientValue macrf)`

Uses of Optimizable.ByGradientValue in cc.mallet.optimize

Subinterfaces of Optimizable.ByGradientValue in cc.mallet.optimize
`static interface` | `Optimizable.ByHessian`

Classes in cc.mallet.optimize that implement Optimizable.ByGradientValue
`class` | `OptimizableCollection.ByGradientValue`

Methods in cc.mallet.optimize with parameters of type Optimizable.ByGradientValue
`boolean` | `OptimizerEvaluator.ByGradient.evaluate(Optimizable.ByGradientValue maxable, int iter)` Performs some operation at the end of each iteration of a maximizer.

Constructors in cc.mallet.optimize with parameters of type Optimizable.ByGradientValue
`BackTrackLineSearch(Optimizable.ByGradientValue optimizable)`
`ConjugateGradient(Optimizable.ByGradientValue function)`
`ConjugateGradient(Optimizable.ByGradientValue function, double initialStepSize)`
`GradientAscent(Optimizable.ByGradientValue function)`
`GradientBracketLineOptimizer(Optimizable.ByGradientValue function)`
`LimitedMemoryBFGS(Optimizable.ByGradientValue function)`
`OptimizableCollection.ByGradientValue(Optimizable.ByGradientValue... ops)`
`OrthantWiseLimitedMemoryBFGS(Optimizable.ByGradientValue function)`
`OrthantWiseLimitedMemoryBFGS(Optimizable.ByGradientValue function, double l1wt)`

Uses of Optimizable.ByGradientValue in cc.mallet.optimize.tests

Methods in cc.mallet.optimize.tests with parameters of type Optimizable.ByGradientValue
`static boolean` | `TestOptimizable.testValueAndGradient(Optimizable.ByGradientValue maxable)` Tests that getValue and getValueGradient are consistent.
`static double` | `TestOptimizable.testValueAndGradientCurrentParameters(Optimizable.ByGradientValue maxable)` Tests that the value and gradient function are consistent at the current parameters.
`static double` | `TestOptimizable.testValueAndGradientInDirection(Optimizable.ByGradientValue maxable, double[] direction)`
`static boolean` | `TestOptimizable.testValueAndGradientRandomParameters(Optimizable.ByGradientValue maxable, java.util.Random r)` Tests that getValue and getValueGradient are consistent at a random parameter setting.

Uses of Optimizable.ByGradientValue in cc.mallet.topics

Classes in cc.mallet.topics that implement Optimizable.ByGradientValue
`class` | `DMROptimizable`

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES