Class NaiveBayesModel

java.lang.Object

opennlp.tools.ml.model.AbstractModel

opennlp.tools.ml.naivebayes.NaiveBayesModel

All Implemented Interfaces:

opennlp.tools.ml.model.MaxentModel

public class NaiveBayesModel
extends opennlp.tools.ml.model.AbstractModel

A MaxentModel implementation of the multinomial Naive Bayes classifier model.

See Also:

• AbstractModel
• MaxentModel

Constructor Summary

Constructors

Constructor	Description
NaiveBayesModel(opennlp.tools.ml.model.Context[] params, String[] predLabels, String[] outcomeNames)	Initializes a NaiveBayesModel.

Method Summary

Modifier and Type	Method	Description
static double[]	eval(int[] context, double[] prior, opennlp.tools.ml.model.EvalParameters model)	Evaluates a NaiveBayesModel.
double[]	eval(String[] context)
double[]	eval(String[] context, double[] probs)
double[]	eval(String[] context, float[] values)
double[]	eval(String[] context, float[] values, double[] outsums)

Methods inherited from class opennlp.tools.ml.model.AbstractModel

equals, getAllOutcomes, getBestOutcome, getDataStructures, getIndex, getModelType, getNumOutcomes, getOutcome, hashCode

Methods inherited from class Object

getClass, notify, notifyAll, toString, wait, wait, wait

Constructor Details

NaiveBayesModel

public NaiveBayesModel(opennlp.tools.ml.model.Context[] params,
 String[] predLabels,
 String[] outcomeNames)

Initializes a NaiveBayesModel.

Parameters:

params - The parameters to set.

predLabels - The predicted labels.

outcomeNames - The names of the outcomes.

Method Details

eval

public double[] eval(String[] context)

eval

public double[] eval(String[] context,
 float[] values)

eval

public double[] eval(String[] context,
 double[] probs)

eval

public double[] eval(String[] context,
 float[] values,
 double[] outsums)

eval

public static double[] eval(int[] context,
 double[] prior,
 opennlp.tools.ml.model.EvalParameters model)

Evaluates a NaiveBayesModel.

Parameters:

context - The context parameters as int[].

prior - The data prior to the evaluation as double[].

model - The EvalParameters used for evaluation.

Returns:

The resulting evaluation data as double[].