Search results
A Confusion Matrix is a popular representation of the performance of classification models. The matrix (table) shows us the number of correctly and incorrectly classified examples, compared to the actual outcomes (target value) in the test data.
With this confusion matrix calculator, we aim to help you to calculate various metrics that can be used to assess your machine learning model's performance. The confusion matrix is the most prevalent way of analyzing the results of a classification machine learning model.
Draw confusion matrix for classes.
Confusion Matrix Generator developed by Damiano Perri, Phd, Research Fellow at the University of Perugia. This page allows you to create confusion matrices and obtain a usable image in papers. The resulting images are of high resolution and high quality.
This confusion matrix calculator determines several statistical measures linked to the performance of classification models and is particularly useful in research.
Enter classification results to compute multi-class accuracy, precision, recall, and F1 score online.
Tool to calculate statistical data (sensitivity, specificity, precision, predictive value, etc.) from true positives, true negatives, false positives, false negatives values, also called confusion matrix.
Oct 11, 2024 · Enter your data into the calculator. Click the 'Calculate' button to see your confusion matrix. Review the matrix results for insights on your model's performance. Use the metrics provided to make informed decisions on model adjustments.
This calculator helps you compute key performance metrics of classification models based on the confusion matrix. How to Use: Enter the values for True Positive (TP), False Positive (FP), True Negative (TN), and False Negative (FN). Click the “Calculate” button to get the results.
Compute answers using Wolfram's breakthrough technology & knowledgebase, relied on by millions of students & professionals. For math, science, nutrition, history, geography, engineering, mathematics, linguistics, sports, finance, music….
