Package opennlp.tools.ml.perceptron
Class SimplePerceptronSequenceTrainer
- java.lang.Object
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- opennlp.tools.ml.AbstractTrainer
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- opennlp.tools.ml.AbstractEventModelSequenceTrainer
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- opennlp.tools.ml.perceptron.SimplePerceptronSequenceTrainer
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- All Implemented Interfaces:
Trainer
,EventModelSequenceTrainer<Event>
public class SimplePerceptronSequenceTrainer extends AbstractEventModelSequenceTrainer
Trainsmodels
with sequences using the perceptron algorithm.Each outcome is represented as a binary perceptron classifier. This supports standard (integer) weighting as well average weighting.
Sequence information is used in a simplified was to that described in: Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with the Perceptron Algorithm. Michael Collins, EMNLP 2002.
Specifically only updates are applied to tokens which were incorrectly tagged by a sequence tagger rather than to all feature across the sequence which differ from the training sequence.
- See Also:
PerceptronModel
,AbstractEventModelSequenceTrainer
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Field Summary
Fields Modifier and Type Field Description static String
PERCEPTRON_SEQUENCE_VALUE
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Fields inherited from class opennlp.tools.ml.AbstractTrainer
ALGORITHM_PARAM, CUTOFF_DEFAULT, CUTOFF_PARAM, ITERATIONS_DEFAULT, ITERATIONS_PARAM, TRAINER_TYPE_PARAM, VERBOSE_DEFAULT, VERBOSE_PARAM
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Fields inherited from interface opennlp.tools.ml.EventModelSequenceTrainer
SEQUENCE_VALUE
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Constructor Summary
Constructors Constructor Description SimplePerceptronSequenceTrainer()
Instantiates aSimplePerceptronSequenceTrainer
with a default configuration of training parameters.
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Method Summary
All Methods Instance Methods Concrete Methods Deprecated Methods Modifier and Type Method Description AbstractModel
doTrain(SequenceStream<Event> events)
boolean
isValid()
Deprecated.Usevalidate()
instead.void
nextIteration(int iteration)
AbstractModel
trainModel(int iterations, SequenceStream<Event> sequenceStream, int cutoff, boolean useAverage)
Trains aPerceptronModel
with given parameters.void
validate()
Checks the configuredparameters
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Methods inherited from class opennlp.tools.ml.AbstractEventModelSequenceTrainer
train
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Methods inherited from class opennlp.tools.ml.AbstractTrainer
getAlgorithm, getCutoff, getIterations, init, init
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Field Detail
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PERCEPTRON_SEQUENCE_VALUE
public static final String PERCEPTRON_SEQUENCE_VALUE
- See Also:
- Constant Field Values
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Constructor Detail
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SimplePerceptronSequenceTrainer
public SimplePerceptronSequenceTrainer()
Instantiates aSimplePerceptronSequenceTrainer
with a default configuration of training parameters.
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Method Detail
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validate
public void validate()
Checks the configuredparameters
. If a subclass overrides this, it should callsuper.validate();
.- Overrides:
validate
in classAbstractTrainer
- Throws:
IllegalArgumentException
- Thrown if the algorithm name is not equal to {PERCEPTRON_SEQUENCE_VALUE
}.
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isValid
@Deprecated public boolean isValid()
Deprecated.Usevalidate()
instead.- Overrides:
isValid
in classAbstractTrainer
- Returns:
true
if the validation of the internal configuration succeeds,false
otherwise.
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doTrain
public AbstractModel doTrain(SequenceStream<Event> events) throws IOException
- Specified by:
doTrain
in classAbstractEventModelSequenceTrainer
- Throws:
IOException
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trainModel
public AbstractModel trainModel(int iterations, SequenceStream<Event> sequenceStream, int cutoff, boolean useAverage) throws IOException
Trains aPerceptronModel
with given parameters.- Parameters:
iterations
- The number of iterations to use for training.sequenceStream
- TheSequenceStream
used as data input.cutoff
- The {AbstractTrainer.CUTOFF_PARAM
} value to use for training.useAverage
- Whether to use 'averaging', or not.- Returns:
- A valid, trained
perceptron model
. - Throws:
IOException
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nextIteration
public void nextIteration(int iteration) throws IOException
- Throws:
IOException
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