Encyclopedia of Systems Biology

2013 Edition
| Editors: Werner Dubitzky, Olaf Wolkenhauer, Kwang-Hyun Cho, Hiroki Yokota

Positive Predictive Value

  • Haiying Wang
  • Huiru Zheng
Reference work entry
DOI: https://doi.org/10.1007/978-1-4419-9863-7_256

Synonyms

Definition

In Machine Learning, the positive predictive value is defined as the proportion of predicted positives which are actual positives. It reflects the probability a predicted positive is a true positive.

Let TP be true positives (samples correctly classified as positive), FN be false negatives (samples incorrectly classified as negative), FP be false positives (samples incorrectly classified as positive), and TN be true negatives (samples correctly classified as negative). The relationship between these prediction outcomes can then be summarized using a confusion matrix (Kohavi and Provost 1998) as illustrated in Table  1.
Positive Predictive Value, Table 1

Sample confusion matrix for two possible outcomes positive and negative

 

Predicted

Positive

Negative

Actual

Positive

TP

FN

Negative

FP

TN

This is a preview of subscription content, log in to check access.

References

  1. Bland M (2000) An introduction to medical statistics, 3rd edn. Oxford University Press, OxfordGoogle Scholar
  2. Hardesty LA, Klym AH, Shindel BE, Chough DM, Sumkin JH, Gur D (2005) Is maximum positive predictive value a good indicator of an optimal screening mammography practice? AJR Am J Roentgenol 184(5):1505–1507PubMedGoogle Scholar
  3. Kohavi R, Provost F (1998) Glossary of terms. Mach Learn 30:271–274Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  1. 1.School of Computing and Mathematics, Computer Science Research InstituteUniversity of UlsterJordanstownUK