Uses of Class cc.mallet.fst.TransducerEvaluator (Mallet 2 API)

Packages that use TransducerEvaluator
Package Description

cc.mallet.fst
Transducers, including Conditional Random Fields (CRFs).

cc.mallet.fst.semi_supervised.tui

Uses of TransducerEvaluator in cc.mallet.fst

Subclasses of TransducerEvaluator in cc.mallet.fst
Modifier and Type	Class	Description
`class`	`CRFWriter`	Saves a trained model to specified filename.
`class`	`InstanceAccuracyEvaluator`	Reports the percentage of instances for which the entire predicted sequence was correct.
`class`	`LabelDistributionEvaluator`	Prints predicted and true label distribution.
`class`	`MultiSegmentationEvaluator`	Evaluates a transducer model, computes the precision, recall and F1 scores; considers segments that span across multiple tokens.
`class`	`PerClassAccuracyEvaluator`	Determines the precision, recall and F1 on a per-class basis.
`class`	`SegmentationEvaluator`
`class`	`TokenAccuracyEvaluator`	Evaluates a transducer model based on predictions of individual tokens.
`class`	`ViterbiWriter`	Prints the input instances along with the features and the true and predicted labels to a file.

Methods in cc.mallet.fst with parameters of type TransducerEvaluator
Modifier and Type	Method	Description
`TransducerTrainer`	TransducerTrainer.`addEvaluator(TransducerEvaluator te)`
`void`	CRF.`evaluate(TransducerEvaluator eval, InstanceList testing)`	Deprecated.
`TransducerTrainer`	TransducerTrainer.`removeEvaluator(TransducerEvaluator te)`
`static void`	SimpleTagger.`test(TransducerTrainer tt, TransducerEvaluator eval, InstanceList testing)`	Test a transducer on the given test data, evaluating accuracy with the given evaluator
`boolean`	HMM.`train(InstanceList ilist, InstanceList validation, InstanceList testing, TransducerEvaluator eval)`
`boolean`	MEMMTrainer.`train(InstanceList training, InstanceList validation, InstanceList testing, TransducerEvaluator eval, int numIterations, int numIterationsPerProportion, double[] trainingProportions)`	Not implemented yet.
`static CRF`	SimpleTagger.`train(InstanceList training, InstanceList testing, TransducerEvaluator eval, int[] orders, java.lang.String defaultLabel, java.lang.String forbidden, java.lang.String allowed, boolean connected, int iterations, double var, CRF crf)`	Create and train a CRF model from the given training data, optionally testing it on the given test data.
`boolean`	CRFTrainerByLabelLikelihood.`trainWithFeatureInduction(InstanceList trainingData, InstanceList validationData, InstanceList testingData, TransducerEvaluator eval, int numIterations, int numIterationsBetweenFeatureInductions, int numFeatureInductions, int numFeaturesPerFeatureInduction, double trueLabelProbThreshold, boolean clusteredFeatureInduction, double[] trainingProportions)`
`boolean`	CRFTrainerByLabelLikelihood.`trainWithFeatureInduction(InstanceList trainingData, InstanceList validationData, InstanceList testingData, TransducerEvaluator eval, int numIterations, int numIterationsBetweenFeatureInductions, int numFeatureInductions, int numFeaturesPerFeatureInduction, double trueLabelProbThreshold, boolean clusteredFeatureInduction, double[] trainingProportions, java.lang.String gainName)`	Train a CRF using feature induction to generate conjunctions of features.
`boolean`	MEMMTrainer.`trainWithFeatureInduction(InstanceList trainingData, InstanceList validationData, InstanceList testingData, TransducerEvaluator eval, int numIterations, int numIterationsBetweenFeatureInductions, int numFeatureInductions, int numFeaturesPerFeatureInduction, double trueLabelProbThreshold, boolean clusteredFeatureInduction, double[] trainingProportions, java.lang.String gainName)`	Not implemented yet.

Method parameters in cc.mallet.fst with type arguments of type TransducerEvaluator
Modifier and Type	Method	Description
`TransducerTrainer`	TransducerTrainer.`addEvaluators(java.util.Collection<TransducerEvaluator> tes)`

Uses of TransducerEvaluator in cc.mallet.fst.semi_supervised.tui

Methods in cc.mallet.fst.semi_supervised.tui with parameters of type TransducerEvaluator
Modifier and Type	Method	Description
`static void`	SimpleTaggerWithConstraints.`test(TransducerTrainer tt, TransducerEvaluator eval, InstanceList testing)`	Test a transducer on the given test data, evaluating accuracy with the given evaluator
`static CRF`	SimpleTaggerWithConstraints.`trainGE(InstanceList training, InstanceList testing, java.util.ArrayList<GEConstraint> constraints, CRF crf, TransducerEvaluator eval, int iterations, double var, int resets)`	Create and train a CRF model from the given training data, optionally testing it on the given test data.
`static CRF`	SimpleTaggerWithConstraints.`trainPR(InstanceList training, InstanceList testing, java.util.ArrayList<PRConstraint> constraints, CRF crf, TransducerEvaluator eval, int iterations, double var)`	Create and train a CRF model from the given training data, optionally testing it on the given test data.