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Confusion matrix

Abstract

Compare the actual values in your data against predicted values in a confusion matrix to understand how your model is performing.

Takes a set of classification predictions and produces a 2x2 confusion matrix. A confusion matrix compares the actual values in your data against the predicted values. In a 2x2 matrix, you'll see:

  • true positives, where the actual value and predicted value are both true.

  • true negatives, where the actual value and predicted value are both false.

  • false positives, where the actual value was false but the prediction was true.

  • false negatives, where the actual value was true but the prediction was false.

When to use this tool

A confusion matrix can help you understand how your model is performing.