Uses of Interface
cc.mallet.optimize.Optimizer

Packages that use Optimizer
cc.mallet.classify Classes for training and classifying instances. 
cc.mallet.fst Transducers, including Conditional Random Fields (CRFs). 
cc.mallet.grmm.learning   
cc.mallet.optimize Classes for finding the maximum of a function. 
 

Uses of Optimizer in cc.mallet.classify
 

Methods in cc.mallet.classify that return Optimizer
 Optimizer MaxEntL1Trainer.getOptimizer()
           
 Optimizer MaxEntGETrainer.getOptimizer()
           
 Optimizer MaxEntTrainer.getOptimizer()
           
 Optimizer ClassifierTrainer.ByOptimization.getOptimizer()
           
 Optimizer MaxEntL1Trainer.getOptimizer(InstanceList trainingSet)
           
 Optimizer MaxEntTrainer.getOptimizer(InstanceList trainingSet)
          This method is called by the train method.
 

Uses of Optimizer in cc.mallet.fst
 

Methods in cc.mallet.fst that return Optimizer
 Optimizer CRFTrainerByValueGradients.getOptimizer()
           
 Optimizer CRFTrainerByLabelLikelihood.getOptimizer()
           
 Optimizer TransducerTrainer.ByOptimization.getOptimizer()
           
 Optimizer CRFTrainerByValueGradients.getOptimizer(InstanceList trainingSet)
          Returns a L-BFGS optimizer, creating if one doesn't exist.
 Optimizer CRFTrainerByLabelLikelihood.getOptimizer(InstanceList trainingSet)
           
 Optimizer CRFTrainerByL1LabelLikelihood.getOptimizer(InstanceList trainingSet)
           
 

Uses of Optimizer in cc.mallet.grmm.learning
 

Methods in cc.mallet.grmm.learning that return Optimizer
 Optimizer DefaultAcrfTrainer.getMaxer()
           
 

Methods in cc.mallet.grmm.learning with parameters of type Optimizer
 void DefaultAcrfTrainer.setMaxer(Optimizer maxer)
           
 

Uses of Optimizer in cc.mallet.optimize
 

Classes in cc.mallet.optimize that implement Optimizer
 class AGIS
           
 class ConjugateGradient
           
 class GradientAscent
           
 class LimitedMemoryBFGS
           
 class OrthantWiseLimitedMemoryBFGS
          Implementation of orthant-wise limited memory quasi Newton method for optimizing convex L1-regularized objectives.