The indices used in evaluating prediction results of this component are described below.

.. list-table::
  :header-rows: 1
  :widths: 1, 1, 3

  * - Evaluation Index
    - Type
    - Description
  * - true_positive
    - int
    - Number of samples determined as **positive** correctly (TP).
  * - false_positive
    - int
    - Number of samples determined as **positive** incorrectly (FP).
  * - true_negative
    - int
    - Number of samples determined as **negative** correctly (TN).
  * - false_negative
    - int
    - Number of samples determined as **negative** incorrectly (FN).
  * - accuracy
    - float
    - | Proportion of **true** results in the population as shown below:
      |
      | :math:`\frac{\mbox{TP} + \mbox{TN}}{\mbox{TP} + \mbox{FP} + \mbox{TN} + \mbox{FN}}`
  * - classification_error
    - float
    - | Proportion of **false** results in the population as shown below:
      |
      | :math:`\frac{\mbox{FP} + \mbox{FN}}{\mbox{TP} + \mbox{FP} + \mbox{TN} + \mbox{FN}} = 1 - \mbox{accuracy}`
  * - precision
    - float
    - | Proportion of the ``true_positive`` against all samples determined as positive as shown below:
      |
      | :math:`\frac{\mbox{TP}}{\mbox{TP} + \mbox{FP}}`
  * - recall
    - float
    - | Proportion of the ``true_positive`` against all the actual positive samples as shown below:
      |
      | :math:`\frac{\mbox{TP}}{\mbox{TP} + \mbox{FN}}`
  * - specificity
    - float
    - | Proportion of the ``true_negative`` against all the actual negative samples as shown below:
      |
      | :math:`\frac{\mbox{TN}}{\mbox{TN} + \mbox{FP}}`
  * - false_positive_rate
    - float
    - | Proportion of the ``false_positive`` against all the actual negative samples as shown below:
      |
      | :math:`\frac{\mbox{FP}}{\mbox{TN} + \mbox{FP}} = 1 - \mbox{specificity}`
  * - false_negative_rate
    - float
    - | Proportion of the ``false_negative`` against all the actual positive samples as shown below:
      |
      | :math:`\frac{\mbox{FN}}{\mbox{TP} + \mbox{FN}} = 1 - \mbox{recall}`
  * - f_measure
    - float
    - | Harmonic mean of ``precision`` and ``recall`` as shown below:
      |
      | :math:`\frac{2 \times \mbox{precision} \times \mbox{recall}}{\mbox{precision} + \mbox{recall}}`
  * - auc
    - float
    - Area under ROC (Receiver Operating Characteristic) curve.
  * - area_under_precision_recall
    - float
    - Area under PR (Precision-Recall) curve.
