Confusion Matrix

What Does Confusion Matrix Mean?

A confusion matrix is a type of table construct that plays a specific role in machine learning and related engineering. It helps to show the prediction and recall in a system where the values of the test data are known.


Techopedia Explains Confusion Matrix

Typically, a confusion matrix treats a binary process of classification. The resulting table is composed of two rows and two columns, filled with four values – true positives, false positives, true negatives and false negatives.

In the confusion matrix, a true positive exists where observation is positive with a positive prediction. A false positive exists where observation is negative, with a positive prediction. A true negative exists where observation is negative with negative prediction, and a false negative indicates a positive observation with a negative prediction.

Assorted equations then show how to calculate accuracy and precision for a given project. Many confusion matrix projects will utilize tools like Python SciKit or Numpy or others.


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Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects to a non-technical, business audience. Over the past twenty years her explanations have appeared on TechTarget websites and she's been cited as an authority in articles by the New York Times, Time Magazine, USA Today, ZDNet, PC Magazine and Discovery Magazine.Margaret's idea of a fun day is helping IT and business professionals learn to speak each other’s highly specialized languages. If you have a suggestion for a new definition or how to improve a technical explanation, please email Margaret or contact her…