org.apache.lucene.classification.utils

## Class ConfusionMatrixGenerator.ConfusionMatrix

- java.lang.Object
- - org.apache.lucene.classification.utils.ConfusionMatrixGenerator.ConfusionMatrix

- Enclosing class:
    ConfusionMatrixGenerator

      public static class ConfusionMatrixGenerator.ConfusionMatrix
      extends Object

  a confusion matrix, backed by a `Map` representing the linearized matrix

- - ### Method Summary

    All Methods Instance Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `double` | `getAccuracy()` Calculate accuracy on this confusion matrix using the formula: accuracy = correctly-classified / (correctly-classified + wrongly-classified)
    `double` | `getAvgClassificationTime()` get the average classification time in milliseconds
    `double` | `getF1Measure()` get the F-1 measure on this confusion matrix
    `double` | `getF1Measure(String klass)` get the F-1 measure of the given class
    `Map<String,Map<String,Long>>` | `getLinearizedMatrix()` get the linearized confusion matrix as a `Map`
    `int` | `getNumberOfEvaluatedDocs()` get the no.
    `double` | `getPrecision()` get the macro averaged precision (see `getPrecision(String)`) over all the classes.
    `double` | `getPrecision(String klass)` calculate precision on the given class
    `double` | `getRecall()` get the macro averaged recall (see `getRecall(String)`) over all the classes
    `double` | `getRecall(String klass)` calculate recall on the given class
    `String` | `toString()`

    - ### Methods inherited from class java.lang.Object

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

- - ### Method Detail

    - #### getLinearizedMatrix

          public Map<String,Map<String,Long>> getLinearizedMatrix()

      get the linearized confusion matrix as a `Map`
      Returns:
        a `Map` whose keys are the correct classification answers and whose values are the actual answers' counts

    - #### getPrecision

          public double getPrecision(String klass)

      calculate precision on the given class
      Parameters:
        `klass` - the class to calculate the precision for
      Returns:
        the precision for the given class

    - #### getRecall

          public double getRecall(String klass)

      calculate recall on the given class
      Parameters:
        `klass` - the class to calculate the recall for
      Returns:
        the recall for the given class

    - #### getF1Measure

          public double getF1Measure(String klass)

      get the F-1 measure of the given class
      Parameters:
        `klass` - the class to calculate the F-1 measure for
      Returns:
        the F-1 measure for the given class

    - #### getF1Measure

          public double getF1Measure()

      get the F-1 measure on this confusion matrix
      Returns:
        the F-1 measure

    - #### getAccuracy

          public double getAccuracy()

      Calculate accuracy on this confusion matrix using the formula: accuracy = correctly-classified / (correctly-classified + wrongly-classified)
      Returns:
        the accuracy

    - #### getPrecision

          public double getPrecision()

      get the macro averaged precision (see `getPrecision(String)`) over all the classes.
      Returns:
        the macro averaged precision as computed from the confusion matrix

    - #### getRecall

          public double getRecall()

      get the macro averaged recall (see `getRecall(String)`) over all the classes
      Returns:
        the recall as computed from the confusion matrix

    - #### toString

          public String toString()

      Overrides:
        `toString` in class `Object`

    - #### getAvgClassificationTime

          public double getAvgClassificationTime()

      get the average classification time in milliseconds
      Returns:
        the avg classification time

    - #### getNumberOfEvaluatedDocs

          public int getNumberOfEvaluatedDocs()

      get the no. of documents evaluated while generating this confusion matrix
      Returns:
        the no. of documents evaluated

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