Package opennlp.tools.doccat

Class DocumentCategorizerME

java.lang.Object

opennlp.tools.doccat.DocumentCategorizerME

All Implemented Interfaces:

DocumentCategorizer

public class DocumentCategorizerME
extends Object
implements DocumentCategorizer

A Max-Ent based implementation of DocumentCategorizer.

Constructor Summary

Constructors

Constructor	Description
DocumentCategorizerME(DoccatModel model)	Initializes a DocumentCategorizerME instance with a doccat model.

Method Summary

Modifier and Type	Method	Description
double[]	categorize(String[] text)	Categorizes the given text, provided in separate tokens.
double[]	categorize(String[] text, Map<String,Object> extraInformation)	Categorize the given text provided as tokens along with the provided extra information.
String	getAllResults(double[] results)	Retrieves the name of the category associated with the given probabilities.
String	getBestCategory(double[] outcome)	Retrieves the best category from previously generated outcome probabilities
String	getCategory(int index)	Retrieves the category at a given index.
int	getIndex(String category)	Retrieves the index of a certain category.
int	getNumberOfCategories()	Retrieves the number of categories.
Map<String,Double>	scoreMap(String[] text)	Retrieves a Map in which the key is the category name and the value is the score.
SortedMap<Double,Set<String>>	sortedScoreMap(String[] text)	Retrieves a SortedMap of the scores sorted in ascending order, together with their associated categories.
static DoccatModel	train(String lang, ObjectStream<DocumentSample> samples, TrainingParameters mlParams, DoccatFactory factory)	Starts a training of a DoccatModel with the given parameters.

Methods inherited from class java.lang.Object

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

Constructor Detail

DocumentCategorizerME

public DocumentCategorizerME(DoccatModel model)

Initializes a DocumentCategorizerME instance with a doccat model. Default feature generation is used.

Parameters:

model - the DoccatModel to be used for categorization.

Method Detail

categorize

public double[] categorize(String[] text,
                           Map<String,Object> extraInformation)

Categorize the given text provided as tokens along with the provided extra information.

Specified by:

categorize in interface DocumentCategorizer

Parameters:

text - The text tokens to categorize.

extraInformation - Additional information for context to be used by the feature generator.

Returns:

The per category probabilities.

categorize

public double[] categorize(String[] text)

Description copied from interface: DocumentCategorizer

Categorizes the given text, provided in separate tokens.

Specified by:

categorize in interface DocumentCategorizer

Parameters:

text - The tokens of text to categorize.

Returns:

The per category probabilities.

scoreMap

public Map<String,Double> scoreMap(String[] text)

Description copied from interface: DocumentCategorizer

Retrieves a Map in which the key is the category name and the value is the score.

Specified by:

scoreMap in interface DocumentCategorizer

Parameters:

text - The tokenized input text to classify.

Returns:

A Map with the score as a key.

sortedScoreMap

public SortedMap<Double,Set<String>> sortedScoreMap(String[] text)

Description copied from interface: DocumentCategorizer

Retrieves a SortedMap of the scores sorted in ascending order, together with their associated categories.

Many categories can have the same score, hence the Set as value.

Specified by:

sortedScoreMap in interface DocumentCategorizer

Parameters:

text - the input text to classify

Returns:

A SortedMap with the score as a key.

getBestCategory

public String getBestCategory(double[] outcome)

Description copied from interface: DocumentCategorizer

Retrieves the best category from previously generated outcome probabilities

Specified by:

getBestCategory in interface DocumentCategorizer

Parameters:

outcome - An array of computed outcome probabilities.

Returns:

The best category represented as String.

getIndex

public int getIndex(String category)

Description copied from interface: DocumentCategorizer

Retrieves the index of a certain category.

Specified by:

getIndex in interface DocumentCategorizer

Parameters:

category - The category for which the index is to be found.

Returns:

The index.

getCategory

public String getCategory(int index)

Description copied from interface: DocumentCategorizer

Retrieves the category at a given index.

Specified by:

getCategory in interface DocumentCategorizer

Parameters:

index - The index for which the category shall be found.

Returns:

The category represented as String.

getNumberOfCategories

public int getNumberOfCategories()

Description copied from interface: DocumentCategorizer

Retrieves the number of categories.

Specified by:

getNumberOfCategories in interface DocumentCategorizer

Returns:

The no. of categories.

getAllResults

public String getAllResults(double[] results)

Description copied from interface: DocumentCategorizer

Retrieves the name of the category associated with the given probabilities.

Specified by:

getAllResults in interface DocumentCategorizer

Parameters:

results - The probabilities of each category.

Returns:

The name of the outcome.

train

public static DoccatModel train(String lang,
                                ObjectStream<DocumentSample> samples,
                                TrainingParameters mlParams,
                                DoccatFactory factory)
                         throws IOException

Starts a training of a DoccatModel with the given parameters.

Parameters:

lang - The ISO conform language code.

samples - The ObjectStream of DocumentSample used as input for training.

mlParams - The TrainingParameters for the context of the training.

factory - The DoccatFactory for creating related objects defined via mlParams.

Returns:

A valid, trained DoccatModel instance.

Throws:

IOException - Thrown if IO errors occurred.