Package opennlp.tools.util.eval

## Class FMeasure

- java.lang.Object
- - opennlp.tools.util.eval.FMeasure

-     public final class FMeasure
      extends Object

  The `FMeasure` is a utility class for `evaluators` which measures 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 | Description
    --- | ---
    `FMeasure()` |

  - ### Method Summary

    All Methods Static Methods Instance Methods Concrete Methods
    Modifier and Type | Method | Description
    --- | --- | ---
    `double` | `getFMeasure()` | `f-measure = 2 * precision * recall / (precision + recall)`.
    `double` | `getPrecisionScore()` |
    `double` | `getRecallScore()` |
    `void` | `mergeInto​(FMeasure measure)` | Merge results into `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()` |
    `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()

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

    - #### getRecallScore

          public double getRecallScore()

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

    - #### getFMeasure

          public double getFMeasure()

      `f-measure = 2 * precision * recall / (precision + recall)`.
      Returns:
        Retrieves the f-measure or `-1` if precision + recall `&lt;= 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 `metric`.
      Parameters:
        `measure` - The `FMeasure` to merge.

    - #### toString

          public String toString()

      Overrides:
        `toString` in class `Object`
      Returns:
        A human-readable `String` representation.

    - #### 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.