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Definition

F1 Score

The F1 Score is a statistical metric used to evaluate a classification model's accuracy. It is calculated as the harmonic mean of precision (exactness) and recall (completeness), making it ideal for datasets with imbalanced classes.

Frequently Asked Questions

What is the formula for F1 Score?

`F1 = 2 * (Precision * Recall) / (Precision + Recall)`.

Why not just use accuracy instead of F1 Score?

Because accuracy can be misleading on imbalanced datasets. If 99% of emails are not spam, a model that classifies everything as non-spam has 99% accuracy but an F1 score of 0.

Quick Facts

  • CategoryMathematical Foundations
  • Key ApplicationClassification model validation, benchmark tracking, and search performance assessment

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