Index (Apache OpenNLP :: Core :: ML :: Naive Bayes 3.0.0-M4 API)

# Index

A B C D E G I L N O P S T W
All Classes and Interfaces|All Packages|Constant Field Values

## A

addIn(double) - Method in class opennlp.tools.ml.naivebayes.LogProbability
  Compounds the existing `probability` mass on the label with the new probability passed in to the method.
addIn(double) - Method in class opennlp.tools.ml.naivebayes.Probability
  Compounds the existing probability mass on the label with the new probability passed in to the method.
addIn(T, double, int) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
  Compounds the existing `probability` mass on the label `t` with the new probability passed in to the method.
addIn(T, double, int) - Method in class opennlp.tools.ml.naivebayes.Probabilities
  Compounds the existing probability mass on the label `t` with the new probability passed in to the method.

## B

BinaryNaiveBayesModelReader - Class in opennlp.tools.ml.naivebayes
  A `NaiveBayesModelReader` that reads models from a binary format.
BinaryNaiveBayesModelReader(DataInputStream) - Constructor for class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelReader
  Instantiates `BinaryNaiveBayesModelReader` via a `DataInputStream` containing the model contents.
BinaryNaiveBayesModelReader(File) - Constructor for class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelReader
  Instantiates `BinaryNaiveBayesModelReader` via a `File` and creates a reader for it.
BinaryNaiveBayesModelWriter - Class in opennlp.tools.ml.naivebayes
  A `NaiveBayesModelWriter` that writes models in a binary format.
BinaryNaiveBayesModelWriter(AbstractModel, DataOutputStream) - Constructor for class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelWriter
  Instantiates `BinaryNaiveBayesModelWriter` via an `naive bayes model` and a `DataOutputStream`.
BinaryNaiveBayesModelWriter(AbstractModel, File) - Constructor for class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelWriter
  Instantiates `BinaryNaiveBayesModelWriter` via an `naive bayes model` and a `File`.

## C

checkModelType() - Method in class opennlp.tools.ml.naivebayes.NaiveBayesModelReader
  Reads the mode type from the underlying reader and informs if it not a `Naive Bayes` model.
close() - Method in class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelWriter
close() - Method in class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelWriter
constructModel() - Method in class opennlp.tools.ml.naivebayes.NaiveBayesModelReader
  Constructs a `model`.

## D

discardCountsBelow(double) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
discardCountsBelow(double) - Method in class opennlp.tools.ml.naivebayes.Probabilities
doTrain(DataIndexer<TrainingParameters>) - Method in class opennlp.tools.ml.naivebayes.NaiveBayesTrainer

## E

eval(int[], double[], EvalParameters) - Static method in class opennlp.tools.ml.naivebayes.NaiveBayesModel
  Evaluates a `NaiveBayesModel`.
eval(String[]) - Method in class opennlp.tools.ml.naivebayes.NaiveBayesModel
eval(String[], double[]) - Method in class opennlp.tools.ml.naivebayes.NaiveBayesModel
eval(String[], float[]) - Method in class opennlp.tools.ml.naivebayes.NaiveBayesModel
eval(String[], float[], double[]) - Method in class opennlp.tools.ml.naivebayes.NaiveBayesModel

## G

get() - Method in class opennlp.tools.ml.naivebayes.LogProbability
get() - Method in class opennlp.tools.ml.naivebayes.Probability
get(T) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
get(T) - Method in class opennlp.tools.ml.naivebayes.Probabilities
getAll() - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
getAll() - Method in class opennlp.tools.ml.naivebayes.Probabilities
getConfidence() - Method in class opennlp.tools.ml.naivebayes.Probabilities
getKeys() - Method in class opennlp.tools.ml.naivebayes.Probabilities
getLabel() - Method in class opennlp.tools.ml.naivebayes.LogProbability
getLabel() - Method in class opennlp.tools.ml.naivebayes.Probability
getLog() - Method in class opennlp.tools.ml.naivebayes.LogProbability
getLog() - Method in class opennlp.tools.ml.naivebayes.Probability
getLog(T) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
getLog(T) - Method in class opennlp.tools.ml.naivebayes.Probabilities
getMax() - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
getMax() - Method in class opennlp.tools.ml.naivebayes.Probabilities
getMaxValue() - Method in class opennlp.tools.ml.naivebayes.Probabilities
getOutcomeTotals() - Method in class opennlp.tools.ml.naivebayes.NaiveBayesEvalParameters
getVocabulary() - Method in class opennlp.tools.ml.naivebayes.NaiveBayesEvalParameters

## I

isLarger(Probability<T>) - Method in class opennlp.tools.ml.naivebayes.LogProbability
isLarger(Probability<T>) - Method in class opennlp.tools.ml.naivebayes.Probability
  Checks if a probability is greater than the old one.
isSortAndMerge() - Method in class opennlp.tools.ml.naivebayes.NaiveBayesTrainer

## L

LogProbabilities<T> - Class in opennlp.tools.ml.naivebayes
  Class implementing the probability distribution over labels returned by a classifier as a log of probabilities.
LogProbabilities() - Constructor for class opennlp.tools.ml.naivebayes.LogProbabilities
LogProbability<T> - Class in opennlp.tools.ml.naivebayes
  A class implementing the logarithmic `Probability` for a label.
LogProbability(T) - Constructor for class opennlp.tools.ml.naivebayes.LogProbability

## N

NAIVE_BAYES_VALUE - Static variable in class opennlp.tools.ml.naivebayes.NaiveBayesTrainer
NaiveBayesEvalParameters - Class in opennlp.tools.ml.naivebayes
  Specialized `parameters` for the evaluation of a naive bayes classifier
NaiveBayesEvalParameters(Context[], int, double[], long) - Constructor for class opennlp.tools.ml.naivebayes.NaiveBayesEvalParameters
NaiveBayesModel - Class in opennlp.tools.ml.naivebayes
  A `MaxentModel` implementation of the multinomial Naive Bayes classifier model.
NaiveBayesModel(Context[], String[], String[]) - Constructor for class opennlp.tools.ml.naivebayes.NaiveBayesModel
  Initializes a `NaiveBayesModel`.
NaiveBayesModelReader - Class in opennlp.tools.ml.naivebayes
  The base class for readers of `models`.
NaiveBayesModelReader(File) - Constructor for class opennlp.tools.ml.naivebayes.NaiveBayesModelReader
  Initializes a `NaiveBayesModelReader` via a `File`.
NaiveBayesModelReader(DataReader) - Constructor for class opennlp.tools.ml.naivebayes.NaiveBayesModelReader
  Initializes a `NaiveBayesModelReader` via a `DataReader`.
NaiveBayesModelWriter - Class in opennlp.tools.ml.naivebayes
  The base class for `NaiveBayesModel` writers.
NaiveBayesModelWriter(AbstractModel) - Constructor for class opennlp.tools.ml.naivebayes.NaiveBayesModelWriter
  Initializes a `NaiveBayesModelWriter` for a `NaiveBayes model`.
NaiveBayesTrainer - Class in opennlp.tools.ml.naivebayes
  Trains `models` using the combination of EM algorithm and Naive Bayes classifier which is described in:
NaiveBayesTrainer() - Constructor for class opennlp.tools.ml.naivebayes.NaiveBayesTrainer
  Instantiates a `NaiveBayesTrainer` with default training parameters.
NaiveBayesTrainer(TrainingParameters) - Constructor for class opennlp.tools.ml.naivebayes.NaiveBayesTrainer
  Instantiates a `NaiveBayesTrainer` with specific `TrainingParameters`.

## O

opennlp.tools.ml.naivebayes - package opennlp.tools.ml.naivebayes

## P

persist() - Method in class opennlp.tools.ml.naivebayes.NaiveBayesModelWriter
  Writes the `perceptron model`, using the `AbstractModelWriter.writeUTF(String)`, `AbstractModelWriter.writeDouble(double)`, or `AbstractModelWriter.writeInt(int)`} methods implemented by extending classes.
PlainTextNaiveBayesModelReader - Class in opennlp.tools.ml.naivebayes
  A `NaiveBayesModelReader` that reads models from a plain text format.
PlainTextNaiveBayesModelReader(BufferedReader) - Constructor for class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelReader
  Instantiates `PlainTextNaiveBayesModelReader` via a `BufferedReader` containing the model contents.
PlainTextNaiveBayesModelReader(File) - Constructor for class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelReader
  Instantiates `PlainTextNaiveBayesModelReader` via a `File` and creates a reader for it.
PlainTextNaiveBayesModelWriter - Class in opennlp.tools.ml.naivebayes
  A `NaiveBayesModelWriter` that writes models in a plain text format.
PlainTextNaiveBayesModelWriter(AbstractModel, BufferedWriter) - Constructor for class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelWriter
  Instantiates `PlainTextNaiveBayesModelWriter` via an `naive bayes model` and a `BufferedWriter`.
PlainTextNaiveBayesModelWriter(AbstractModel, File) - Constructor for class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelWriter
  Instantiates `PlainTextNaiveBayesModelWriter` via an `naive bayes model` and a `File`.
Probabilities<T> - Class in opennlp.tools.ml.naivebayes
  Class implementing the probability distribution over labels returned by a classifier.
Probabilities() - Constructor for class opennlp.tools.ml.naivebayes.Probabilities
Probability<T> - Class in opennlp.tools.ml.naivebayes
  Class implementing the probability for a label.
Probability(T) - Constructor for class opennlp.tools.ml.naivebayes.Probability
  Instantiates a `Probability` with a given `label`.

## S

set(double) - Method in class opennlp.tools.ml.naivebayes.LogProbability
  Assigns a `probability` to a label, discarding any previously assigned probability.
set(double) - Method in class opennlp.tools.ml.naivebayes.Probability
  Assigns a probability to a label, discarding any previously assigned probability.
set(Probability<T>) - Method in class opennlp.tools.ml.naivebayes.LogProbability
  Assigns a `probability` to a label, discarding any previously assigned probability.
set(Probability<T>) - Method in class opennlp.tools.ml.naivebayes.Probability
  Assigns a probability to a label, discarding any previously assigned probability.
set(T, double) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
  Assigns a `probability` to a label `t`, discarding any previously assigned probability.
set(T, double) - Method in class opennlp.tools.ml.naivebayes.Probabilities
  Assigns a probability to a label `t`, discarding any previously assigned probability.
set(T, Probability<T>) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
  Assigns a `probability` to a label `t`, discarding any previously assigned probability.
set(T, Probability<T>) - Method in class opennlp.tools.ml.naivebayes.Probabilities
  Assigns a probability to a label `t`, discarding any previously assigned probability.
setConfidence(double) - Method in class opennlp.tools.ml.naivebayes.Probabilities
  Sets the best confidence with which this set of probabilities has been calculated.
setIfLarger(double) - Method in class opennlp.tools.ml.naivebayes.LogProbability
  Assigns a `probability` to a label, discarding any previously assigned probability, if the new probability is greater than the old one.
setIfLarger(double) - Method in class opennlp.tools.ml.naivebayes.Probability
  Assigns a probability to a label, discarding any previously assigned probability, if the new probability is greater than the old one.
setIfLarger(Probability<T>) - Method in class opennlp.tools.ml.naivebayes.LogProbability
  Assigns a `probability` to a label, discarding any previously assigned probability, if the new probability is greater than the old one.
setIfLarger(Probability<T>) - Method in class opennlp.tools.ml.naivebayes.Probability
  Assigns a probability to a label, discarding any previously assigned probability, if the new probability is greater than the old one.
setIfLarger(T, double) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
  Assigns a `probability` to a label `t`, discarding any previously assigned probability, if the new probability is greater than the old one.
setIfLarger(T, double) - Method in class opennlp.tools.ml.naivebayes.Probabilities
  Assigns a probability to a label `t`, discarding any previously assigned probability, if the new probability is greater than the old one.
setLog(double) - Method in class opennlp.tools.ml.naivebayes.LogProbability
  Assigns a log `probability` to a label, discarding any previously assigned probability.
setLog(double) - Method in class opennlp.tools.ml.naivebayes.Probability
  Assigns a log probability to a label, discarding any previously assigned probability.
setLog(T, double) - Method in class opennlp.tools.ml.naivebayes.LogProbabilities
  Assigns a log `probability` to a label `t`, discarding any previously assigned probability.
setLog(T, double) - Method in class opennlp.tools.ml.naivebayes.Probabilities
  Assigns a log probability to a label `t`, discarding any previously assigned probability.

## T

toString() - Method in class opennlp.tools.ml.naivebayes.LogProbability
toString() - Method in class opennlp.tools.ml.naivebayes.Probabilities
toString() - Method in class opennlp.tools.ml.naivebayes.Probability
trainModel(DataIndexer<TrainingParameters>) - Method in class opennlp.tools.ml.naivebayes.NaiveBayesTrainer
  Trains a `NaiveBayesModel` with given parameters.

## W

writeDouble(double) - Method in class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelWriter
writeDouble(double) - Method in class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelWriter
writeInt(int) - Method in class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelWriter
writeInt(int) - Method in class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelWriter
writeUTF(String) - Method in class opennlp.tools.ml.naivebayes.BinaryNaiveBayesModelWriter
writeUTF(String) - Method in class opennlp.tools.ml.naivebayes.PlainTextNaiveBayesModelWriter

A B C D E G I L N O P S T W
All Classes and Interfaces|All Packages|Constant Field Values