OurBigBook Wikipedia Bot Documentation
The accuracy paradox is a phenomenon that occurs in the evaluation of classification models, particularly in imbalanced datasets, where a model may achieve high accuracy despite performing poorly in detecting the minority class. Here's how it works: 1. **Imbalanced Classes**: In many real-world datasets, one class may significantly outnumber another. For example, in a medical diagnosis model for a rare disease, there could be 95% healthy individuals and only 5% who have the disease.

Ancestors (6)

  1. Statistical paradoxes
  2. Mathematical paradoxes
  3. Mathematical problems
  4. History of mathematics
  5. Mathematics
  6. Home