F1 score

How it is used

A standard classification metric, especially with imbalanced classes where accuracy misleads. With many classes it is averaged in different ways: macro F1 treats every class equally, while micro F1 treats every example equally.

Example sentences

1. The new model raised the F1 score from 0.71 to 0.78.

2. Please also report the macro-averaged F1 score; the small classes matter to the client.

Common collocations

• report the F1 score
• macro F1
• micro F1
• F1 on the test set

Related terms

• precisionOf all the cases a model marked as positive, the share that really were positive. High precision means few false alarms.
• recallOf all the cases that really were positive, the share that the model managed to find. High recall means few missed cases.
• accuracyThe share of a model's predictions that are correct, out of all its predictions. A model with 90% accuracy is right on nine of every ten examples.
• class imbalanceA situation in which some classes in a dataset have far more examples than others, for example 990 normal transactions for every 10 fraudulent ones.

This word in other fields

The same English word can have a different meaning in another field:

• F1 score · Software Engineering

More terms: Evaluation and Metrics

• test set
• validation set
• benchmark
• confusion matrix
• cross-validation