// multi-utility computation suite · offline · instant · precise
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sci.precision-recall-F1-multiclass Calculator
Calculates per-class and macro/weighted F1 scores for multiclass classification from a confusion matrix. Macro F1 treats all classes equally regardless of size — weighted F1 accounts for class imbalance and is more informative for skewed datasets like medical diagnosis.
Inputs
Tp
Reference formula or conversion factor shown for context.
Fp
Reference formula or conversion factor shown for context.
Fn
Reference formula or conversion factor shown for context.
Tn
Reference formula or conversion factor shown for context.
Results
precision
Sample size or count used in the calculation.
recall (sensitivity)
Sample size or count used in the calculation.
F1 score
A numerical rating from the scoring model in use.
accuracy
The fraction of predictions or measurements that are correct. High accuracy is only meaningful when the class distribution is balanced.
Matthews Correlation Coefficient (MCC)
Pearson's r — linear relationship strength and direction. +1: perfect positive. 0: no linear relationship. −1: perfect negative. Rule of thumb: |r| below 0.3 = weak, 0.3–0.7 = moderate, above 0.7 = strong. Correlation does not imply causation.
F1 = 2·P·R/(P+R)
Reference formula or conversion factor shown for context.