F1 score

Definitions

1. The harmonic mean of precision and recall, providing a single metric that balances both. Ranges from 0 to 1, where 1 is perfect. The F1 score is especially useful when class distribution is imbalanced and accuracy alone is misleading — a model predicting 'not fraud' for everything could have 99% accuracy but an F1 near zero for the fraud class.

   In plain English: A single number combining how precise and how thorough a model is. It is a better measure than accuracy when the thing you are looking for is rare.

   Example: The model's accuracy was 97%, but the F1 score for the minority class was only 0.41, exposing how poorly it detected actual churning customers.

Related Terms

• Perplexity
• Benchmark
• benchmark contamination
• confusion matrix
• precision (ML)
• recall (ML)
• K-Nearest Neighbors