ML Engineering Tools
Confusion Matrix Calculator
Enter TP, FP, TN, FN to compute all standard classification metrics with class imbalance detection.
No data is transmitted — everything runs locallyTool
Example — TP=85 · FP=15 · TN=920 · FN=20
Accuracy
96.63%
Precision
0.8500
Recall
0.8095
F1 Score
0.8293
About this tool
Confusion Matrix Calculator
The Confusion Matrix Calculator computes precision, recall, F1, accuracy, specificity, and MCC from confusion matrix values with class imbalance warnings.
• Calculate F1 for a model evaluation report
• Detect accuracy inflation on an imbalanced dataset
• Compare two models at the same operating threshold
• Generate metrics for a PR or paper table
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FAQ
What does this tool tell you?
The Confusion Matrix Calculator computes precision, recall, F1, accuracy, specificity, and MCC from confusion matrix values with class imbalance warnings.
What affects the result most?
Confusion matrix: TP, FP, TN, FN — foundation for all classification metrics. Accuracy = (TP+TN)/(TP+TN+FP+FN) — misleading on imbalanced classes. Precision = TP/(TP+FP) — of predicted positives, how many are correct.
How should I use the result?
The calculation is deterministic — the same inputs always produce the same output — so the most useful workflow is to vary one input at a time and see which factor moves the result most. That tells you where to focus your attention before committing to a decision.
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