Confusion Matrix Calculator
Our confusion matrix calculator helps you to calculate all the metrics you need to assess the performance of your mac...
What Confusion Matrix Calculator does
A confusion matrix calculator that computes all standard classification metrics from entered true and predicted values. Users input counts for true positive, false positive, false negative, and true negative, and the tool outputs accuracy, precision, recall, F1 score, true positive rate, false positive rate, false negative rate, false discovery rate, and Matthews correlation coefficient. The site also provides educational context about confusion matrices and their role in evaluating classification models. Results can be shared via a link. The interface presents each metric on a separate line with clear labels, and includes action buttons to clear all entries, reload the calculator, or share the result. A brief explanation of what a confusion matrix is and how to interpret it is included on the page, making it accessible to those learning the concept for the first time.
How to use the Omni Calculator Confusion Matrix Calculator
- 1
Enter the true positive count in the designated field
- 2
Enter the false positive count in the designated field
- 3
Enter the false negative count in the designated field
- 4
Enter the true negative count in the designated field
- 5
View the computed metrics such as accuracy, precision, recall, and F1 score displayed below the inputs
Best for
Data scientists, analysts, and students evaluating the performance of a classification machine learning model who need quick computation of multiple metrics from a confusion matrix.
Limitations
- Results depend on the accuracy of manually entered counts
- No unit switching or data import options available
- Metrics are estimates based on the provided counts
Confusion Matrix Calculator FAQ
- What metrics does the confusion matrix calculator provide?
- The calculator provides accuracy, precision, recall, F1 score, true positive rate, false positive rate, false negative rate, false discovery rate, and Matthews correlation coefficient based on the four confusion matrix values.
- Can I use the calculator without knowing the four confusion matrix values?
- The tool requires the four values—true positive, false positive, false negative, and true negative—to compute any metrics; entering only some values will not produce results.
- Is there an explanation of how to interpret the confusion matrix on the page?
- Yes, the page includes a section explaining what a confusion matrix is in machine learning and how to interpret it using the four base metrics to assess model performance.
- Can I share the calculated results with others?
- The calculator includes a share result feature that allows users to generate a link to the current calculation and settings.
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