Package de.jungblut.classification.bayes

Class MultinomialNaiveBayes

java.lang.Object

de.jungblut.classification.AbstractPredictor

de.jungblut.classification.AbstractClassifier

de.jungblut.classification.bayes.MultinomialNaiveBayes

All Implemented Interfaces:

Classifier, Predictor

public final class MultinomialNaiveBayes
extends AbstractClassifier

Multinomial naive bayes classifier. This class now contains a sparse internal representations of the "feature given class" probabilities. So this can be scaled to very large text corpora and large numbers of classes easily. Serialization and deserialization happens through the like-named static methods.

Author:

thomas.jungblut

Constructor Summary

Constructors

Constructor	Description
MultinomialNaiveBayes()	Default constructor to construct this classifier.
MultinomialNaiveBayes(boolean verbose)	Pass true if this classifier should output some progress information to STDOUT.

Method Summary

Modifier and Type	Method	Description
static MultinomialNaiveBayes	deserialize(java.io.DataInput in)	Deserializes a new MultinomialNaiveBayesClassifier from the given input stream.
de.jungblut.math.DoubleVector	predict(de.jungblut.math.DoubleVector features)	Classifies the given features.
static void	serialize(MultinomialNaiveBayes model, java.io.DataOutput out)
void	train(java.lang.Iterable<de.jungblut.math.DoubleVector> features, java.lang.Iterable<de.jungblut.math.DoubleVector> outcome)	Trains this classifier with the given features and the outcome.

Methods inherited from class de.jungblut.classification.AbstractClassifier

train

Methods inherited from class de.jungblut.classification.AbstractPredictor

extractPredictedClass, extractPredictedClass, predictedClass, predictedClass, predictProbability

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface de.jungblut.classification.Predictor

asClassifier, extractPredictedClass, extractPredictedClass, predictedClass, predictedClass, predictProbability

Constructor Detail

MultinomialNaiveBayes

public MultinomialNaiveBayes()

Default constructor to construct this classifier.

MultinomialNaiveBayes

public MultinomialNaiveBayes(boolean verbose)

Pass true if this classifier should output some progress information to STDOUT.

Method Detail

train

public void train(java.lang.Iterable<de.jungblut.math.DoubleVector> features,
                  java.lang.Iterable<de.jungblut.math.DoubleVector> outcome)

Description copied from interface: Classifier

Trains this classifier with the given features and the outcome. This is the streaming method for training, it takes parallel iterables.

Specified by:

train in interface Classifier

Overrides:

train in class AbstractClassifier

outcome - the outcome must have classes labeled as doubles. E.G. in the binary case you have a single element and decide between 0d and 1d. In higher dimensional cases you have each of these single elements mapped to a dimension.

predict

public de.jungblut.math.DoubleVector predict(de.jungblut.math.DoubleVector features)

Description copied from interface: Predictor

Classifies the given features.

Returns:

the vector that contains an indicator at the index of the class. Usually zero or 1, in some cases it is a probability or activation value.

deserialize

public static MultinomialNaiveBayes deserialize(java.io.DataInput in)
                                         throws java.io.IOException

Deserializes a new MultinomialNaiveBayesClassifier from the given input stream. Note that "in" will not be closed by this method.

Throws:

java.io.IOException

serialize

public static void serialize(MultinomialNaiveBayes model,
                             java.io.DataOutput out)
                      throws java.io.IOException

Throws:

java.io.IOException