Package opennlp.tools.ml.naivebayes
Class NaiveBayesModel
java.lang.Object
opennlp.tools.ml.model.AbstractModel
opennlp.tools.ml.naivebayes.NaiveBayesModel
- All Implemented Interfaces:
MaxentModel
A
MaxentModel
implementation of the multinomial Naive Bayes classifier model.- See Also:
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Nested Class Summary
Nested classes/interfaces inherited from class opennlp.tools.ml.model.AbstractModel
AbstractModel.ModelType
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Constructor Summary
ConstructorDescriptionNaiveBayesModel
(Context[] params, String[] predLabels, String[] outcomeNames) Initializes aNaiveBayesModel
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Method Summary
Modifier and TypeMethodDescriptionstatic double[]
eval
(int[] context, double[] prior, EvalParameters model) Evaluates aNaiveBayesModel
.double[]
Evaluates acontext
.double[]
Evaluates acontext
.double[]
Evaluates acontext
with the specified contextvalues
.double[]
Methods inherited from class opennlp.tools.ml.model.AbstractModel
equals, getAllOutcomes, getBestOutcome, getDataStructures, getIndex, getModelType, getNumOutcomes, getOutcome, hashCode
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Constructor Details
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NaiveBayesModel
Initializes aNaiveBayesModel
.- Parameters:
params
- Theparameters
to set.predLabels
- The predicted labels.outcomeNames
- The names of the outcomes.
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Method Details
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eval
Evaluates acontext
.- Parameters:
context
- An array of String names of the contextual predicates which are to be evaluated together.- Returns:
- An array of the probabilities for each of the different
outcomes, all of which sum to
1
.
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eval
Evaluates acontext
with the specified contextvalues
.- Parameters:
context
- An array of String names of the contextual predicates which are to be evaluated together.values
- The values associated with each context.- Returns:
- An array of the probabilities for each of the different
outcomes, all of which sum to
1
.
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eval
Evaluates acontext
.- Parameters:
context
- An array of String names of the contextual predicates which are to be evaluated together.probs
- An array which is populated with the probabilities for each of the different outcomes, all of which sum to 1.- Returns:
- An array of the probabilities for each of the different
outcomes, all of which sum to
1
.
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eval
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eval
Evaluates aNaiveBayesModel
.- Parameters:
context
- The context parameters asint[]
.prior
- The data prior to the evaluation asdouble[]
.model
- TheEvalParameters
used for evaluation.- Returns:
- The resulting evaluation data as
double[]
.
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