opennlp.tools.util.eval

Class FMeasure

java.lang.Object

opennlp.tools.util.eval.FMeasure

public final class FMeasure
extends Object

The FMeasure is an utility class for evaluators which measure precision, recall and the resulting f-measure. Evaluation results are the arithmetic mean of the precision scores calculated for each reference sample and the arithmetic mean of the recall scores calculated for each reference sample.

Constructor Summary

Constructors

Constructor and Description
FMeasure()

Method Summary

Modifier and Type	Method and Description
double	getFMeasure() Retrieves the f-measure score.
double	getPrecisionScore() Retrieves the arithmetic mean of the precision scores calculated for each evaluated sample.
double	getRecallScore() Retrieves the arithmetic mean of the recall score calculated for each evaluated sample.
void	mergeInto(FMeasure measure) Merge results into fmeasure metric.
static double	precision(Object[] references, Object[] predictions) Calculates the precision score for the given reference and predicted spans.
static double	recall(Object[] references, Object[] predictions) Calculates the recall score for the given reference and predicted spans.
String	toString() Creates a human read-able String representation.
void	updateScores(Object[] references, Object[] predictions) Updates the score based on the number of true positives and the number of predictions and references.

Methods inherited from class java.lang.Object

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

Constructor Detail

FMeasure

public FMeasure()

Method Detail

getPrecisionScore

public double getPrecisionScore()

Retrieves the arithmetic mean of the precision scores calculated for each evaluated sample.

Returns:

the arithmetic mean of all precision scores

getRecallScore

public double getRecallScore()

Retrieves the arithmetic mean of the recall score calculated for each evaluated sample.

Returns:

the arithmetic mean of all recall scores

getFMeasure

public double getFMeasure()

Retrieves the f-measure score. f-measure = 2 * precision * recall / (precision + recall)

Returns:

the f-measure or -1 if precision + recall <= 0

updateScores

public void updateScores(Object[] references,
                         Object[] predictions)

Updates the score based on the number of true positives and the number of predictions and references.

Parameters:

references - the provided references

predictions - the predicted spans

mergeInto

public void mergeInto(FMeasure measure)

Merge results into fmeasure metric.

Parameters:

measure - the fmeasure

toString

public String toString()

Creates a human read-able String representation.

Overrides:

toString in class Object

Returns:

the results

precision

public static double precision(Object[] references,
                               Object[] predictions)

Calculates the precision score for the given reference and predicted spans.

Parameters:

references - the gold standard spans

predictions - the predicted spans

Returns:

the precision score or NaN if there are no predicted spans

recall

public static double recall(Object[] references,
                            Object[] predictions)

Calculates the recall score for the given reference and predicted spans.

Parameters:

references - the gold standard spans

predictions - the predicted spans

Returns:

the recall score or NaN if there are no reference spans