# F1 Score Calculator (simple to use)

F1 score is a common error metric for classification machine learning models. There are several ways to calculate F1 score, in this post I will provide you calculators for the three most common ways of doing so

F1 score is a common error metric for classification predictions. There are several ways to calculate F1 score, in this post are calculators for the three most common ways of doing so.

**The three calculators available are:**

- Calculate using lists of predictions and actuals
- Calculate using precision and recall
- Calculate using confusion matrix

## F1 score calculator using lists of predictions and actuals

This calculator will calculate the F1 score using lists of predictions and their corresponding actual values.

The values in these lists should be integers separated by commas, with the positive label defined.

## F1 score calculator using precision and recall

This calculator will calculate the F1 score by using the Precision and Recall values of the model's predictions.

## F1 score calculator using confusion matrix

This calculator will calculate the F1 score using the sum of True Positive (TP), False Positive (FP) and False Negative (FN) values from the model's predictions.

## Related articles

### Classification metrics

AUC score

Accuracy score

Balanced accuracy

### Classification metric comparisons

F1 score vs AUC

F1 score vs accuracy

Micro vs Macro F1 score

### Metric calculators

Accuracy calculator

R squared calculator

Precision recall calculator

Confusion matrix calculator

Confusion matrix maker

## References

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