Confusion (Error) Matrix Calculator

Inputs

Counts · non-negative integers

Pred. Positive

Pred. Negative

Actual
Positive

True Positive

False Negative

Actual
Negative

False Positive

True Negative

Green = correct · Red = incorrect

F-β weight

Quick examples

Results

Total samples: —

Accuracy ACC

—

(TP + TN) / N

Matthews CC MCC

—

(TP·TN − FP·FN) /
√((TP+FP)(TP+FN)(TN+FP)(TN+FN))

F-β score F1

—

(1+β²)·P·R / (β²·P + R)

Predictive values

Precision PPV

—

TP / (TP + FP)

Neg. Pred. Value NPV

—

TN / (TN + FN)

False Disc. Rate FDR

—

FP / (FP + TP) = 1 − PPV

False Omission FOR

—

FN / (FN + TN) = 1 − NPV

True / false rates

Sensitivity TPR · Recall

—

TP / (TP + FN)

Specificity TNR

—

TN / (TN + FP)

False Pos. Rate FPR

—

FP / (TN + FP) = 1 − TNR

False Neg. Rate FNR

—

FN / (TP + FN) = 1 − TPR

Class distribution & error

Positive prevalence

—

(TP + FN) / N

Negative prevalence

—

(TN + FP) / N

Balanced Accuracy

—

(TPR + TNR) / 2

Error rate

—

(FP + FN) / N = 1 − ACC

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