Evaluating Classification Models: Accuracy, Precision, Recall and F1

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About Course

A model that is “95% accurate” can still be useless. Learn how to read a confusion matrix and calculate accuracy, precision, recall, false positive rate and F1 score, with fully worked examples, and how to choose the right measure for problems such as fraud detection, medical screening and spam filtering.

Tutwoo is an independent learning provider. This course is written from the official documentation and guidance listed in the sources, which can change, so always check the current version. It is not endorsed by any of the organisations listed and is not an accredited qualification.

© 2026 Tutwoo UK Limited. This course was created in-house by Tutwoo and is our original work. It is for your own learning only: please do not copy, share, record or resell it.

What Will You Learn?

  • Build and read a confusion matrix of true and false positives and negatives
  • Calculate accuracy, precision, recall, false positive rate and F1
  • Explain why accuracy misleads on imbalanced data
  • Choose metrics and thresholds that match the real-world cost of errors

Course Content

Course Lessons

  • The confusion matrix
  • Accuracy and why it can mislead
  • Precision, recall and false positive rate
  • F1 score and choosing metrics

Sources & Further Reading
The official guidance this course is based on.

Final Assessment

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