Confusion Matrix Generator developed by Dr. Damiano Perri, Ph.d., Adjunct Professor at the Department of Mathematics and Computer Science, University of Perugia, Italy
This page enables the creation of confusion matrices and the generation of high-resolution, high-quality images suitable for inclusion in academic papers.
The page also calculates many statistics of crucial importance during data analysis.
All calculations are performed locally within your browser, ensuring that no data is transmitted to the server.
No data you enter will be stored, retained or saved.
If you found this page useful and appreciate the project I have developed, I kindly ask that you reference the work for which this tool was created in your next publication:
Perri, D.; Simonetti, M.; Gervasi, O. Synthetic Data Generation to Speed-Up the Object Recognition Pipeline. Electronics 2022, 11, 2. https://doi.org/10.3390/electronics11010002
The page also calculates many statistics of crucial importance during data analysis.
All calculations are performed locally within your browser, ensuring that no data is transmitted to the server.
No data you enter will be stored, retained or saved.
If you found this page useful and appreciate the project I have developed, I kindly ask that you reference the work for which this tool was created in your next publication:
Perri, D.; Simonetti, M.; Gervasi, O. Synthetic Data Generation to Speed-Up the Object Recognition Pipeline. Electronics 2022, 11, 2. https://doi.org/10.3390/electronics11010002
Draw confusion matrix for classes.
1) ↑↑ Set the number of classes and press "apply" ↑↑
2) Click with the mouse on the left cells to set the class names
3) Set absolute values
4) The matrix will automatically calculate the remaining values and you can save it as a PNG picture by pressing the "Download picture" button
Numerical precision:
2) Click with the mouse on the left cells to set the class names
3) Set absolute values
4) The matrix will automatically calculate the remaining values and you can save it as a PNG picture by pressing the "Download picture" button
Numerical precision:
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0 0% |
Statistical measures:
Numerical precision: | List of the formulas used | |
| Precision | TP (TP + FP) |
| Recall also called Sensitivity |
TP (TP + FN) |
| F1 Score | 2*Precision*Recall Precision + Recall |
| Macro-F1 | average of F1 Scores |
| Weighted-F1 | weighted-averaged of F1 Scores |
| Misclassification Rate |
# incorrect predictions # total predictions |