Negative Prediction

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:
    • a Correct Negative Prediction (a True Positive Prediction)
    • an Incorrect Negative Prediction (a False Positive Prediction).
• 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.

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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.

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