# Negative Prediction

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A Negative Prediction is a Test Case Prediction (by a Binary Classification Model) with a label of false.

**AKA:**Predicted as Negative.**Context:**- It can be:

**See:**Positive Prediction.**Example(s):**- a prediction that a Dice Roll Experiment will result in a

**Counter-Example(s):**- any Positive Prediction.

**See:**RMS, Estimation Function, Predictive Relation.

## References

### 2006

- (Fawcett, 2006) ⇒ Tom Fawcett. (2006). “An Introduction to ROC Analysis.” In: Pattern Recognition Letters, 27(8). doi:10.1016/j.patrec.2005.10.010
- QUOTE: Given a classifier and an instance, there are four possible outcomes. If the instance is positive and it is classified as positive, it is counted as a
*true positive*; if it is classified as negative, it is counted as a*false negative*. If the instance is negative and it is classified as negative, it is counted as a*true negative*; if it is classified as positive, it is counted as a*false positive*. Given a classifier and a set of instances (the test set), a two-by-two*confusion matrix*(also called a contingency table) can be constructed representing the dispositions of the set of instances.

- QUOTE: Given a classifier and an instance, there are four possible outcomes. If the instance is positive and it is classified as positive, it is counted as a