Close this search box.

Glossary of Artificial Intelligence (AI), Machine Learning (ML), and Big Data Terms

Confusion Matrix

A method for determining the accuracy and precision of a classifier model by determining the total number of true positives, true negatives, false positives, and false negative results and placing the results in a grid table. The confusion matrix provides key evaluation statistics including recall, precision, accuracy, specificity, sensitivity, F1 score, and other measures of model performance. It’s important to determine which measure has the most value for a particular model. Unfortunately there’s no easy way to compare algorithms purely on one measure, as there are are many tradeoffs!

Get Certified on the Proven Path to Success with AI, Big Data & Analytics Projects

Login Or Register


Register to View Event


Get The Confusion Matrix


AI Best Practices

Get the Step By Step Checklist for AI Projects


Login to register for events. Don’t have an account? Just register for an event and an account will be created for you!